The Perception Deception - cs4fn: · PDF fileComputer Science for Fun Issue 5 Special Issue on The Perception Deception Computer Science Illusions Special Issue on Computer Science

Computer Science for Fun Issue 5

Special Issue on

ThePerceptionDeceptionComputer Science Illusions

Special Issue on

ThePerceptionDeceptionComputer Science Illusions

Face Off – Changing Faces

the Computer Science Way

Face Off – Changing Faces

the Computer Science Way

ISSN 1754-3657 (Print)ISSN 1754-3665 (Online)

Pub0607 CS4FN Issue 5 V3.qxd 18/5/07 16:53 Page 1

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Welcome to cs4fn

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How do I knowyou’re telling the truth?In this edition of cs4fn we look at illusions, how they work and their links tocomputer science. This area of science, like all of science, doesn’t have all thecorrect answers. What science does is to give good answers that fit the currentevidence. Of course how you put the evidence together and the conclusions you drawfrom them may change over time.

Suppose you find, in a field, two smallpieces of coal and a carrot close together.What happened here? From the evidenceyou might claim that in fact there had beena snowman in the field, with coal eyes anda carrot nose. The snowman had meltedand this was all that was left. Your evidencesupports the ‘snowman hypothesis’, ahypothesis being a posh Greek word for asuggested explanation. Now supposesomeone else comes along, they look at theevidence and they come up with the ‘twovans hypothesis’ that it was caused by acoal truck passing the field and loosing twobits of coal, then a vegetable truck passingby and dropping a carrot. Which hypothesisis correct?

The coal and carrot mystery

Sorry no can do, but how about….

In this issue:

Pg4 Pepper’s Ghost

Pg 8 How to fake a super brain

Pg 10 Face Off – Changing faces

Pg16 Sensational – the try’em at homeguide to illusions

My hypothesis is better thanyours!

Suppose now that you check the recentweather and find it was recently snowingthere. That could give more clout to the‘snowman hypothesis’, but equally well inthe winter people need more coal for heatand carrots to make hot soup, so therewould be more vans. That means the ‘twovan hypothesis’ could still easily be correct.What’s needed is an experiment to findsome new evidence to separate the twohypotheses, and see which is better. Anexperiment is proposed: build a timemachine (or create your own Primeval styleanomaly) and go back and see whatactually happened. That will settle thingsonce and for all. But no! That’s rejected:you can’t find a police box big enough onthe inside. So what next?

Because of reasons like limitations intechnology we can’t do exactly theexperiment we want so we have to come upwith experiments we can do. Back in ourfield the ‘find a truck track’ experiment isproposed. If the ‘two van hypothesis’ iscorrect then it follows there should beevidence of van tyre tracks near by. Anexpedition is sent, but to ensure fair playthey aren’t told what to look for. If they didknow they were after tyre tracks that couldprejudice them. They might be trying sohard they mistake some other muddypattern for tyre tracks. The team return withtheir new evidence. They found tyre trackson the road just at the side of the field, overthe hedge where no one had bothered tolook before, and what’s more there were bitsof coal and carrots all over the place, and a‘beware rough road surface’ sign. Result!


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Cover Illusion: The cover illusion is calledthe Scintillating grid illusion. Stare atone point on the grid – other points willflash!

Wake Up! Fix It!She owns a chain of very posh hotels. She is not happy. You are going to fix it though aren't you. Well aren't you?

The problem is nothing is actually broken. Everything works just as intended. So what's the problem? The guests keep complaining. They can’t work the hotel alarm clocks. One was late for a meeting.Another was woken in the middle of the night…The complaints keep coming. It is not that anything is broken, just too hard to use.

That is why you've been called in. You are a Usability Expert and she has had enough. She founded the hotel chain on ‘total customer care’ - everything perfect. Stress-free. No hassle. The gadgets were supposed to help not hinder. She wants a new design.

Go to the cs4fn webzine’s (www.cs4fn.org) online usability workshop to find out more and try your hand as a usability expert, learn about science based techniques like Walkthroughs and Wizard-of-Oz studies.

True orfalsification?

Science can never say never. That’s whyit’s such a dynamic and exciting field.Theories have to fit the existingevidence, but the ideas change as new evidence comes to light. Newdiscoveries change the world and thepeople in it. There are also sociologistsand philosophers who study the way thatscience works on a personal level. Afterall science is done by people andscientists have all the usual humancharacteristics. One philosopher ofscience, Karl Popper, argued that goodscientific theories need to be able to beproved wrong. For example, my theory is ‘all cats are grey’. Someone can falsifythis by showing me Eddy a lovely tabbycat, cute but certainly not grey! Until anon-grey cat turns up though (if ever)the theory is fine.

Viva the scientificrevolution

Thomas Kuhn, who studied the historyof science, argues that science movesforward through political revolutions. At any one time there are theories thateveryone believes. This is called thenormal science phase and scientistswork day to day with the currenttheories. However scientists who don’tagree, don’t get published so easily, and find it hard to get any money to doresearch. All the effort goes into thecurrent way of thinking (or paradigm).Slowly over a period of time the currenttheories make wrong predictions, errorsturn up, they are ignored, till eventuallythere are too many to ignore. A crisisensues, and a paradigm shift occurs.Everyone starts to believe the newtheory, and the normal science phasebegins again… till the next big jump.

Victory is mine, or is it?

The ‘two van hypothesis’ works. Itexplains everything. Oh says the‘snowman hypothesis’ camp, that’s notright. The kids who built the snowmancame in a truck to the fields, and theyhad extra coal and carrots in their pocketsand that fell out when they were gettingout of the van shaking because they hadbeen bounced by the bumpy road. At thispoint you’re probably thinking that soundsa bit silly. Of course it could be true that there areuntidy, traumatised, snowman buildingkids in vans, but probably it’s more likelythat the ‘two van hypothesis’ is correct.You can’t be 100 per cent certain,though. Okay, so let\s try a newexperiment why don’t we ….

We leave the field at this stage. It’sgetting late and the two camps are stillarguing away, coming up with moreexperiments, accumulating more data andevidence, following the scientific method.

Every illusion explanation in this editionneeds to be considered in the light of thescientific method, as does every scientificresult. What’s the evidence to support theclaim? It is because science is built on an ever-increasing foundation of evidencethat it is so powerful and is able to giveus our understanding of the world aroundus today. It may have its limitations, andcan never give answers with 100 per centcertainty. After all there may be somemissing piece of the puzzle, but it hasachieved some wonderful triumphs. Butscience never rests. You can (andprobably do) apply the scientific processconstantly in your day to day life; youhave a view on things (hypothesis) andare constantly testing these with newevidence from new experiences(experiments). You don’t always takethings for granted, you ask questions, like scientists do. We can always expectthe unexpected.

PS: I never thought that my snowmanbuilding would cause such problems! Perhaps I should mention it to someone?



When Pepper’s Ghost firstappeared on the stage aspart of one of ProfessorPepper’s shows onChristmas Eve, 1862 itstunned the audiences.This was more than justmagic: it was miraculous.It was so amazing thatsome spiritualists wereconvinced Pepper haddiscovered a way of reallysummoning spirits. A ghostly figure appearedon the stage out of thinair, interacted with theother characters on thestage and thendisappeared in an instant.This was no dark séancewhere ghostly effectshappen in a darkenedroom: who knows whattricks are then beingpulled in the dark tocause the effects. Neitherwas it modern day specialeffects where it is all doneon film or in the virtualworld of a computer. Thiswas on a brightly lit stagein front of everyone’seyes…

Switch to the modern day and similarghostly magic is now being used byfighter pilots. Has the military beenfunding X-files research? Well maybe, but there is nothing supernatural aboutPepper’s Ghost. It is just an illusion. The show it first appeared in was aScience show, though it went on to amazeaudiences as part of magic shows foryears to come, and can still be found, for example in Disney Theme Parks, andto make Virtual band Gorillaz come to lifeonstage and perform with Madonna.

Today’s ‘supernatural’ often becomestomorrow’s reality, thanks to technology.With Pepper’s ghost, 19th century magichas in fact become enormously useful in21st century hi-tech. 19th centurymagicians were more than just showmen,they were inventors, precision engineersand scientists, making use of the latestscientific results, frequently pushingtechnology forward themselves. Peopleoften think of magicians as beingsecretive, but they were alsobusinessmen, often patenting theinventions behind their tricks, makingthem available for all to see but alsoensuring their rivals could not use themwithout permission. The magic behindPepper’s ghost was patented by HenryDircks, a Liverpudlian engineer, in 1863as a theatrical effect though it wasprobably originally invented much earlier– it was described in an Italian book backin 1558 by Baptista Porta.

So what was Pepper’s ghost? It’s a clichéto say that “it’s all done with mirrors”,but it is quite amazing what you can dowith them if you both understand theirphysics and are innovative enough tothink up extraordinary ways to use oldideas. Pepper’s ghost worked in acompletely different way to the normalway mirrors are used in tricks though. Itwas done using a normal sheet of glass,not a silvered mirror at all. If you haveever looked at your image reflected in awindow on a dark night you have seen aweak version of Pepper’s Ghost. The trick

was to place a large, spotlessly cleansheet of glass at an angle in front of thestage between the actors and theaudience. By using the stage lights in justthe right way, it becomes a half mirror.Not only can the stage be seen throughthe glass, but so can anything placed atthe right position off the stage where theglass is pointing. Better still, because ofthe Physics of reflection, the reflectedimages don’t seem to be on the surface of the glass at all, but the same distancebehind as the objects are in front. Theactor playing the ghost would perform ina hidden black area so that he or she wasthe only thing that reflected light fromthat area. When the ghost was to appear a very strong light was shone on the actor.Suddenly the reflection would appear –and as long as they were standing theright distance from the mirror, they couldappear anywhere desired on the stage. To make them disappear in an instant thelight was just switched off.

Jump to the 21st century and a similartechnique has reappeared. Now theghosts are instrument panels. A problemwith controlling a fighter plane is youdon’t have time to look down. You reallywant the data you need to keep control ofyour plane wherever you are lookingoutside the plane. It needs not just to bein the right position on the screen but atthe right depth so you don’t need torefocus your eyes. Most importantly youmust also be able to see out of the planein an unrestricted way…You need thePeppers Ghost effect. That is all ‘Head-up’ displays do, though the precisetechnology used varies.

Satnav systems in cars are very dangerousif you have to keep looking down to seewhere the thing actually means you toturn. “What? This left turn or the nextone?” Use a Head-up display and theinstructions can hover in front of you.Better still you can project a yellow line(say) as though it was on the road,showing you the way off into the distance:Follow the Yellow Brick Road … Oh andwasn’t the Wizard of Oz another greatmagician who used science andengineering rather than magic dust?

Go to the cs4fn webzine to see how to makeyour own Pepper’s Ghost magic box.

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Pepper’s Ghost

With Pepper’s ghost,19th century magic

has in fact becomeenormously useful

21st century hi-tech


Some ‘big game hunters’think the greatest huntingthrill is to hunt a lion.Much more excitingsurely would by to huntwith a pack of lions... outon the school playingfield.Mobile technology is now everywhere butwhat kind of new experiences are nowpossible? How can mobile technology bestbe used to make school more fun? Whatmatters most to make learning engaging:Complicated graphics? Authenticchallenges? Precise location awareness?

A team from Futurelab, the BBC's NaturalHistory Unit, Hewlett Packard, theUniversity of Bristol and the Mixed RealityLab at the University of Nottinghamdecided to explore these issues with anovel way to learn. They realised that theBBC's huge amounts of wildlife footage,when combined with state-of-the-art mobilephone technology, could be used as thebasics of lessons in animal behaviour thatwere as much a game as they were a class.Enter the lions.

The way the Virtual Savannah works is thatthe class spend the day acting out beinglionesses, trying to live on the Savannah. To survive they must behave like real lions,marking out territory (done by spraying ...guess what!), hunting as a pack (theultimate in team-work challenges) neededto eat that day, and surviving the dryseason. All this is done on the playingfields. As the trainee ‘lions’ move aroundthe playing field, their mobiles keep track of where they are on the Savannah,showing them pictures of theirsurroundings including other nearbyanimals. The lions signal to each otherusing the handset (so don't worry ‘spraying’for the virtual lions is done at the touch of abutton!) To survive the challenges theparticipants can spend as much time backin the classroom as they wish learning howthey must behave to survive. Lots ofresources are available but which ones theyuse is up to them. If the virtual lionessesstruggle over a challenge, such as huntingas a pack, then they can, if they like, goback inside and learn more to improve.

Not the way a lion learns maybe, but stilleffective!

The Savannah experience was trialled on aclass of year 7 pupils who thought it wasway better than normal lessons. The classhad fun and learnt. The researchers,meanwhile, found that engaging learningexperiences don't actually need lots offancy graphics or hardware like virtualreality headsets. A minimal amount of videoand audio can transport people to a virtualworld outside their normal experience. Ourimaginations are enough to fill in the rest ofthe illusion. What matters most is that thechallenge itself is a real and engaging one.

So in future, rather than watching a DavidAttenborough film about your favouriteanimals you could actually be out therebeing one – though if you are an antelope:watch out for those lions – they are prettygood at it now.

Often given away free in comics, X-rayspecs supposedly give you Superman’spower of seeing through solid objects. Theywere a trick of course but the reality isactually far more interesting than the myth.

Making a spectacle of yourselfThe glasses are normally a big colourfulcardboard spectacle frame, the ‘lenses’ ofwhich are made with two layers ofcardboard with a small hole in the middle.You look at the world through these holes,but unknown to you embedded in betweenthe cardboard layers of the lenses, coveringthe holes is a bit of bird feather. It’s thefeather, with a bit of physics and the helpof your brain that makes them ‘work’!

Going feather into X-ray specsThe veins of a feather are semi transparentand grow very tightly together. This ribbedstructure is so dense that light coming inthrough the holes is diffracted. That is, it’sbent slightly by the structure of the featherveins. This causes the wearer to see twoslightly displaced and blurry images of theworld. Looking at a pencil for example yousee two offset images. When your braincombines these together you get a darkerimage in the overlap. You interpret this asbeing able to see the graphite in the pencilor the bones in your hand. Well sort of.

Invisible fish anyone?It was American mail order marketer HaroldNathan Braunhut who invented X-rayspecs. He also ‘invented’ and sold invisiblegoldfish. These were non-existent fish thatwere guaranteed to remain invisiblepermanently, which was a fairly transparentmarketing ploy that you can see rightthrough!

The illusionof superpowers –X-rayspecs

The Virtual Savannah

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NewDirections

We can start to buildcomputer models of howhumans perceive a wholerange of properties of thescene like movement,colour, or slopes(orientations). When itcomes to slopes we knowthat in your brain youmeasure the orientation ateach point in the scene atseveral different angles, ratherthan just at one or two. This brainstructure is called an orientationcolumn, and is probably there to helpour computation be more robust. Modellingthese orientation columns, and building acomputer model as close to the biology aspossible allows two things.

First we can see if our model performs likea human would. We can predict from ourmodel how a human would see a particularpattern, then test with a real human to seeif we were right. If we were, then our modelgot something right, and we have a betterunderstanding of how our brains compute.Secondly since the model is mathematicalit doesn’t matter if it’s run on biological‘stuff’ like your brain, or on electronics‘stuff’ in a computer, so we can buildcomputer vision systems with human-like abilities.

Your brain is doing some amazingcalculations as you read these words. Not only are you recognising the letters, theupright and top cross of the 'T', but you arealso understanding what those letters meanwhen put together. Computer Scientists arelooking at how our brains work to buildbetter machines with the same kinds ofskills. One area where people are far betterthan current technology is in seeing. Aroundhalf your brain is estimated to be involved inprocessing some type of information fromyour eyes. It takes a lot of computing powerfor us to see and understand what we see,whether it’s faces, letters or even a caféwall (but more of that wall later).

Bits of Brains

Scientists have recently started to get abetter understanding of the early stages ofvision, but seeing is a complex process andthere is much more to discover. Your visualcortex at the back of your brain takes thenerve signals from your eyes and starts tocalculate with them. From this calculationsome of the basic ‘building blocks’ ofseeing are created. We see things movingand in colour, and we also know veryaccurately how the parts of the scene weare looking at slope. Slopes, or spatialorientations, are a very important part ofthe early visual calculations. Slopes tell ussomething about an object, a rectangulartable for example has straight edges, andslopes also tell us something about how faran object is away and how it's positioned in the scene. Think of the table again. Ifyou are looking straight down on it all thesides are parallel. If you are looking from a distance the sides seam to slope. It’s called perspective and was one of the keydiscoveries that made Renaissance art inthe middle ages so realistic.

Usefulillusions

So where does the café wall come into this? If you look at a brick wall you cansometimes get a strange effect. The straight lines of the mortar cansometimes look sloped. It's an opticalillusion. Your brain is making a ‘mistake’ in its slope calculations.

A mathematical model developed byresearchers at Queen Mary suffers thesame sorts of mistakes. It miscalculates like a human does, and in effect it is‘seeing’ the illusion too... and because anoptical illusion is an unusual miscalculationfor our brains to make, the fact that themodel makes the same mistakes is usefulevidence for us to say that the modelsomehow has caught the essence of thehuman brain calculations. Now we havebuilt part of a brain we can use it for manydifferent computer vision applications.

Biology has found some great solutions tohard engineering and computing problems.Now we can use them in our machines too.

Getting anangle on the brain

Around half yourbrain is involved

in processinginformation from

your eyes


Understanding how our brain works ingoing from measurements of physicalthings like light wavelength, which is thestarting point for vision, or changes in airpressure, the starting point for sound, tocreate the perceptions of seeing andhearing is a fascinating fundamentalproblem. All this information comes into our brain and somehow it turns into ourperception of the world, but how on earthdoes it do it? At present we have someclever ideas, and some intriguing clues, but the problem has not been solved yet.

To try and unravel this human mystery willtake many more years of hard work, and itwill need a range of different skills; from the psychologists doing experiments to themathematicians and computer scientiststrying to build and test computersimulations of the process, but clever clueslike the illusion of the McGurk effect canhelp us along the way. It is also important if we are to build computers and robots thatwe find more naturally easy to talk with. It suggests they need to get more than just the sounds right, but the lips too!


The facebase rapexperimentTry this one at home

You and two friends can experiment withthe McGurk effect yourself. One of yourfriends is the OBSERVER. Have them lookdirectly at your face, and have your otherfriend, let’s call them the HIDDENSPEAKER, stand behind the OBSERVER sothe OBSERVER can’t see their face.

Now start to silently and repeatedly mouththe monosyllabic word (that is one syllableword) ‘face’. At the same time yourHIDDEN SPEAKER friend behind theOBSERVER says the word ‘base’ over andover again (you might want to use handsignals to synchronise the actions, so thehidden speaker wags their finger to set thebeat). After about ten repetitions stop andask your OBSERVER what they ‘hear’ –they should ‘hear’ face (even though baseis the word being spoken!). Now try itagain, but this time have your OBSERVERclose their eyes. As they can’t be confusedby what they see they should just hear‘base’.

Experiment with what happens if you askyour observer to open and close their eyeswhile you and the hidden speaker aredoing your ‘base’, ‘face’ rap. The theorypredicts that when the observer can seethe word ‘face’ being mouthed that’s whatthey will hear. Try using differentmonosyllabic words, or syllables like Baand Pa, or even try having the observerclose their eyes and feel the person’s face.Perhaps you can come up with your ownidea to test… that’s how research works.

Who knows? You might find a new clue tohelp unlock the secrets of the brain!

Say have youheard the oneabout theMcGurk effect?We normally think about sight and sound asbeing different senses. What we hear andwhat we see are independent of each other.So it was something of a surprise whenresearchers discovered that what we seecan actually change what we hear.

The McGurk Effect, named after HarryMcGurk, one of the researchers who firstdiscovered this strange reality, shows thatwhat you see is what you hear. Theexperiments involved taking videos ofpeople saying various different syllables.Syllables such as Ba and Ga are soundsthat are the building blocks of all spokenwords. The videos were edited to replacethe recorded sound with anotherprerecorded syllable sound. The new editedvideo was then played to an observer andthey were asked what the person in thevideo was saying. What the researchersfound was that observers always go for thesyllable they see being spoken on the videorather than the actual sound being heard.

This effect is very general, it works withpeople from all language backgrounds,young children, or even when you mix maleand female faces and voices. What thisstrange McGurk illusion shows is that ourbrain is using the visual information to workwith even when it’s in direct contradictionto the actual sound. Your eyes help youhear. Stranger still the effect has also beenshown to work when observers touch ratherthan look at the face, so it’s not just aboutsight.


Fun withFibonaccisequencesWould you like to be able to impress yourfriends and family with your amazingmathematical skills? Now is your chance.Here is a rather cunning maths magictrick that uses the power of somethingcalled a Fibonacci sequence to do all thehard work for you.

Performing the amazingmathematical brain trickFirst select a person to impress. Ask themto write down any two numbers (say bothless than 30) one under the other. Supposethey chose the numbers 16 and 21. Theywrite these two numbers under each other:

1621

Now ask them to add these two numberstogether and write the total under the firsttwo numbers. After a bit of mentalarithmetic they write:

162137

Now you ask them, having just added thefirst and second, to add the secondnumber to the third number in the list: that is 21+37 for our example. They mustwrite that new total under the numbers inthe list. So they now have:

16213758

Now we step up a gear. Have them do thissame thing again and again, adding thelast two numbers each time until thereare ten numbers in the list. They mayneed to resort to button pressing on acalculator. That’s fine, and all the betterto show your maths super powers if theyare finding it hard. Look away while theyare doing the later numbers, so they don’tthink you are up to anything. When theyhave ten numbers in the list you turnback and prepare to impress.

The final list of 10 for our example lookslike this:

1621 37 58 95 153 248 401 649 1050

You are going to instantly find the sum ofthese ten numbers. They can start to addthem on their calculator, but you will beatthem to the answer, “It’s 2728,” you say,and what’s more, after the buttons arepressed and the additions done on theirmachine they see you are right!

I’d like tothank…But how has this illusion of super mathspower been possible? Well it’s all down tothe genius of the sixth century Indianmathematician Virahanka and thethirteenth century Italian mathematicianLeonardo Pisano. Leonardo Pisano isbetter known by his nickname Fibonacci,and that is where the term ‘Fibonaccisequence’ comes from.

Adding the first and second numbers toget the third number in the sequencethen adding the second and thirdnumbers to get the fourth number, and soon creates a Fibonacci sequence, andthese number sequences have some veryspecial properties. Let’s look at the trick.How can you do the sum so quickly? Wellthe sum of all ten numbers every time isjust eleven times the fourth number fromthe bottom, and multiplying by 11 is easyeven without a calculator – you justmultiply by ten and add the number backagain! So 11x248 is 2480+248 … 2728and that’s the trick! But of course what’simportant with any trick is that you reallyknow for sure it will always work and I’mnot just making it up. You wouldn’t wantit to go wrong in front of an audience,would you?

Prove it then!Okay, so I’ll prove it! What could possiblygo wrong? Well the only free choices arethe starting numbers (16 and 21 here), so you can check that my claim of 11times the fourth number from the bottomof a list of ten is correct, but we’ve seenthat’s true for those numbers. Whathappens if the person picks othernumbers? Well we could try checking allpossible number combinations, but hey,you have a life, so lets use somecomputational thinking here.

Rather than use specific numbers let’s getall abstract and mathematical. Lets callthe first two numbers A and B. That waythey can be anything! So lets see how thesequence builds up with these. It’s simply a case of adding the A’s and B’s, so forexample the third term is the sum of Aand B. That’s easy it’s A+B. The fourth is B+ (A+B) = A+2B, and so on, writing it out in full we have:

ABA + BA + 2B

2A + 3B3A + 5B5A + 8B8A + 13B

13A + 21B21A + 34B

55A + 88B

So we now know that the sum of 10terms, starting with A and B (whateverthey actually are) is 55A+88B, but look atthe value of the fourth number up fromthe bottom. It’s 5A + 8B, and what do weget if we multiply 5A + 8B by 11? That’sright it is 55A + 88B, the total sum! Sothe trick works because there issomething mathematically special aboutadding up exactly ten numbers from aFibonacci sequence and we now know forsure that it will work for any two startingvalues A and B. Sorted!

How to fake a super brain



Pure Fibonacci numbers (the sequencestarting: 1,1,2,3,5,8,13,…) crop up innature a lot – count the number of petals on a flower: “She loves, me. She loves, me not,She loves me…” Whether she loves you or not, the chancesare the count of petals was a Fibonaccinumber (Daisies usually have 34, 55 or 89petals, for example – all Fibonaccinumbers). It isn’t magic, but due to thestructure of the natural process that leads to their formation. The sequence crops up inthe family trees of bees too, because of theway male and female bees breed – a factthat is used in the book The Da Vinci Code.Unfortunately author Dan Brown got thedetails wrong, as computer scientist, HaroldThimbleby of Swansea has pointed out (seethe webzine).

Computer scientists like the Fibonaccisequence because it is a good example ofsomething that can be programmed easilyusing what is known as recursion.Recursion just means you define somethingusing a simpler version of itself: If we writethe fifth Fibonacci number (which isactually 8) as fib(5), the fourth as fib(4) and so on then we can calculate it as:

Define fib(5) = fib(4) + fib(3)

That tells a computer to calculate fib(5) bycalculating fib(4) and fib(3) first and addthem together. fib(4) and fib(3) are workedout in the same way. We can write this towork for any number (lets call it n) as:

Define fib(n)=fib(n-1)+fib(n-2)

We then just have to say how to do thesimple cases:

Define fib(1)=1

Define fib(0)=1

You can write your own recursive programsthat draw pictures based on recursivepatterns. In fact the man-woman picture(right) is drawn by a program using aFibonacci recursion, just drawing men orwomen instead of adding numbers…andthe picture shows what happens when beesbreed too. See the webzine for more detailand for how to use the free GeomLabsoftware from Oxford University to writeprograms that draw like this usingrecursion.

She Loves Me… She Loves Me NotShe Loves Me…She Loves Me Not




The computerscience ofchanging facesThe gory plot line of the 1997 movieFace/Off staring John Travolta and NicolasCage, involves what was then the sciencefiction medical process of a face transplant.Government agent Sean Archer must find aticking bomb planted by terrorist CasterTroy. To do this he takes on the identity ofTroy by having Caster’s face surgicallytransferred onto him so he can infiltrate theterrorist’s group in prison. Just to complicatethings the real Troy (the baddy) latermanages to get hold of Archer’s (the goody)face and pretending to be Archer helps histwin brother, Pollox Troy escape from prison.The real Archer is left in prison, looking likethe baddy, while Caster, looking like thegoody, goes off to destroy all the documentsthat would prove that the swap ever tookplace. If he’s successful Archer will be leftwith Caster’s Identity to rot in jail. TypicalJohn Woo (the director) action follows withlots of two-handed gun shooting and chases.Eventually it all gets sorted, but it all goesto prove that faces are a key part of ourpersonal identity and that shifting themaround can be very confusing.

Meanwhile medical science has progressedto the stage where we can actuallysuccessfully transplant a face to helppeople whose own faces have beendisfigured. Computer Scientists are alsodeveloping a way to digitally create andtransfer faces, (in a less gruesome way)which could open up some fascinating new applications.

The psychology of faces

Humans seem to have a special part of thebrain to process faces. Since we are socialanimals it’s obviously important that we areable to recognise friends and family, and tobe able to tell from their expressions whatkind of mood they are in. Psychologistshave studied how we use facial informationfor years, and have discovered that it’s farfrom easy. Your brain is doing a lot ofdifficult calculations and using lots ofassumptions to make the job easier. Forexample, when looking at faces we tend tothink of them as convex, that is bulgingoutwards towards us, which of course theynormally do. The brain is so convinced that

faces are convex that even when we look atthe inside of a mask we see a solid face –the hollow face illusion. See page 12 formore on this. The way our faces move isalso very important. It’s been found that ifyou use motion tracking (see page 12) totransfer the movements from an individualonto a computer generated face, eventhough that computerised face isgenderless (looking as much female asmale), observers can tell the gender of theoriginal person from the pattern ofmovements alone; women and men havedifferent ways of moving their faces.

Identikit faces

This idea that we can build faces fromcomponent parts is at the heart of theidentikit process used to try to reconstructthe face of a criminal in a policeinvestigation. In the original system thewitness was given a book filled withdifferent eyes, ears, noses, mouth, hairlinesand so on, and from this they selected theparts that they believed were like those ofthe criminal. It had some success. Theproblem though is that we tend not to seefaces like that. We don’t see them as acombination of bits. We see them as wholefaces, and so often the identikit picturescreated bit by bit didn’t really look like thecriminal at all. The computer-based E-Fitsystem tries to overcome this by takingaccount of some of the psychology of facerecognition. By running the processelectronically the face building elementsstored in the database can be blendedtogether to form a realistic looking face.One problem is that the witness buildingthe face needs to say what isn’t quite rightwith it. That can be difficult. A softwaresystem called Evo-Fit, developed in thePsychology Department at the University ofStirling, overcomes this by creating a rangeof similar faces rather than a single face.The witness selects the ones that areclosest to the criminal. That is often easierto do. The system then uses geneticalgorithms; simplecomputer models forbiological evolution, tobreed more similar faces,and step-by-step, thesystem lets the witnessfocus in on the bestlikeness.

Face off



Now suppose we do the same with goodyagent Sean Archer: take lots of videos ofhim and put this set of videos thorough thePrinciple Component Calculating Machine.We could now paint new Archer videos.Suppose instead we take a video of Archerpulling a particularly silly face. We can takethis single video and work out the mix ofArcher Principle Component videos that heuses to do this. In effect we have aninstruction list of how to add and subtractthe Archer components to make Archerlook silly.

Now we take this instruction list fromArcher but apply it to combine CasterTroy’s’ video components instead. Theresult: a new video where the baddy pullsexactly the same funny face – a face henever pulled in reality! We have takenArcher’s facial movements andtransplanted them onto Troy’s face withouta scalpel. The illusion is complete: Archer’sface can work Troy’s face like a puppet,and there is nothing he can do about it.

Facing up to the future

Apart from applications in espionage, thesetechniques could be used to allow, forexample, actors to impersonate otherpossibly dead actors, of even let youpretend to be someone else on you mobilevideo phone. You would download thecomponents for your new face, and thenjust send the instructions on how to build it.You could even create a face ‘graphicsequaliser’ where rather than mixing musictogether by a set of sliders you mix facialexpressions to create subtle performancesfor computer generated actors.

With computer science, virtually nothing can be taken at face value.

The principle of PrincipleComponents

The Evo-Fit system works by having, not adatabase full of different ears, noses, eyesand so on, but a database containingsomething more cunning. It contains‘Principle Components’ of faces.

Principle Components are produced by astatistical technique that helps us representlots of complicated data in a simplifiedform. We can think of pictures of faces asbeing represented as a collection ofnumbers (after all that’s how they arestored as the pixels of a computer screen).A single good-quality image can containmany thousands of numbers. If wecombine a set of many different faceimages, the amount of data becomesgigantic, and each new face added will addmore muddle to this big set of numbers; allfaces are still in there it’s just that they areall mixed up. We need some way to reducethis muddle so that we have just a fewimages that capture as much of the useful‘face stuff’ in the full set as possible. That’swhere statistics comes in.

You may already have come across theidea of standard deviation or variance inmaths lessons. These values are calculatedfrom the data you are analysing andindicate how spread out the numbers are.A large variance shows that most of thenumbers are spread out. A small varianceshows that they are close together. We canuse similar mathematical tricks on our setof face images. What we want to do is finda few images that will account for the mostvariation in the data; after all it is thevariations in the data that makes the facesdifferent from each other.

Once we turn the handle on the PrincipleComponent Calculating Machine what weget out is a set of images. The first image(the first ‘Principle Component’) accountsfor most of the variation in the data, thesecond Principle Component accounts forthe next highest level of variation and soon. So rather than having to store all theimages in the original set we can just storeas many Principle Component images aswe need (this is called data reduction).What’s more we can add and subtractthese Principle Component images to let usrecreate a good approximation to any of theoriginal faces that we mangled together inthe first place (this is called datareconstruction).

Face painting

If all this maths is a little confusing, think ofit this way. You know from art class that youcan make any colour by mixing togetheramounts of red, green and blue paint (theprimary colours). Think of the PrincipleComponent images as computer calculated‘primary colours’, which you can mixtogether to ‘paint any colour’ – or in thiscase make any face. The fact that thePrinciple Component images are all faces(of a sort) rather than colours means thatthey have the standard overall arrangementof the face. That means the Evo-Fitsoftware doesn’t have a problem ofmistakenly adding in a nose where itshouldn’t belong. The system just movesthrough painting new faces with thePrinciple combinations of the Componentimages until the best match to the criminalis found.

Let’s get moving

We can also apply the Principle Componenttrick to sets of videos of faces, becausevideos are just a series of still frames allstacked together. Of course this means theamount of data involved is even bigger, butit can be done. What comes out of thePrinciple Component Calculating Machinehere is not static images but video images.The first Principle Component videoaccounts for most of the variation in theoriginal set of videos, the second PrincipleComponent video accounts for... and youknow the rest. So we can now ‘paint’ withthese videos to create new videosequences, by combining the appropriatePrinciple Component videos – and that’sexactly what computer science researchersat Queen Mary and psychologists at UCL did!

The Digital Face/Offillusion

Suppose we take lots ofvideo of one person, sayCaster Troy, talking andlaughing in typical baddystyle and put this set ofvideos thorough thePrinciple ComponentCalculating Machine. What wehave are videos that will let uspaint new videos of CasterTroy by combining thecomponents. If we cancombine the right set ofcomponents we canmake his face dowhatever we want,even give us acheery smile.


14Passionate about computer science?

www.cs4fn.org

How does the physical world influence themind? It’s a profound question central tohuman experience that has troubledphilosophers through the centuries. Wesense the physical world around us, through,for example, measuring light intensity in theeye, detecting changes in air pressure in theear, detecting changes in pressure on ourskin, detecting chemicals in the air in ournose or chemicals in our food with ourtongue; but how does this physicalstimulation become a feeling of weight, or ofhearing words or of tasting delicious food?How does the measurement of the stimulusby the body become the experience ofperception in the mind?

We still don’t know the full answer, butback in 1860 a German doctor called ErnstHeinrich Weber, working with a colleagueGustav Fechner, discovered somethingrather fascinating. There is a simplemathematical rule (equation) relating thestrength of stimulation to the strength of theperception, and it works across a wholerange of our senses. This rule is calledWeber’s Law, and it’s one of the firstexamples of a mathematical model relatingbody to mind. It’s also interesting that whileit was actually Fechner who did the maths,he gave the law as a ‘gift’ to Weber whosename it still carries today.

A weightypsychophysicsexperimentWeber carried out several classicexperiments to help him devise the rule. He blindfolded a man and gave him aweight to hold. Slowly Weber added moreweight to the man’s hand, until the manindicated he could first feel a difference.The weight was the stimulus strength, and the ability of the man to notice thedifference in weight was the measure of a

hand), and we can just notice the change ifwe increase the strength by amount dS,(remember dS is the amount of extraweight we add when we notice it), then(dS/S) = k where k is a constant, a numberyou can work out from the experimentaldata.

I predict that…If we measure the constant k for oneparticular weight (by taking themeasurements and doing the division), we can then test if it is really the same forother weights. Better still we can makepredictions to test. Suppose we do it for alow initial weight of 10g where we can justnotice when 1g extra is added. Weber’s lawsays 1g/10g is a constant - here 0.1. Usingthis experimental constant, 0.1, we canpredict how much we should be able toadd to the hand (dS) if we started with 1kg (1000g). The law says (dS/1000) must equal 0.1, so changing the subject of the formula dS = 0.1x1000 = 100g. Our mathematics has made a specificmind/body prediction we can now go and test. Just using descriptive words we couldn’t achieve this useful ability.

Useful all round ruleExperimentally, psychophysics researchershave found that, if you don’t go toextremes, then Weber’s law is a goodpredictor relating stimulus strength toperception. The law holds for weight, lightbrightness, sound loudness and even linelength and has many applications incomputing, for example in image displays,computer graphics and audio processing.Weber’s law is all around us, though youmay not have noticed. Ask yourself this,why cant you see the stars in the daytime?They are shining just as brightly as at night.Why don’t you notice the ticking of a clockin the noisy daytime when it’s there in thesilence of the night? It’s all just Weber’s lawhard at work.

change in his perception. What Weberfound was that the amount of extra weighthe could add until the man could justnotice the difference depended on howmuch weight there was in the hand at thestart. If the weight was say only 10g to startwith, adding 1g more was noticeable, if thestarting weight was say 1kg, then an extra1g added wasn’t perceived. This type ofexperiment where you manipulatesomething in the real physical world andmeasure the perception caused in aperson’s mind is called psychophysics, and it was Weber and Fechner who started this whole field of research.

Say it with mathsIn words, Weber’s law says the stronger theoriginal stimulus, the larger the change youneed to make to notice that any thing haschanged. Words are always useful andWeber could describe his findings, butlooking at the experimental data Fechnerwas able to find a wonderfully simplemathematic description as well. If we callthe stimulus strength S, (for example herethis would be the original weight in the

A mathematicalmodel of the mind




The Illusion ofIntelligence?

Not everyone agrees that the Turing test isreally about intelligence. Manyresearchers believe it is just about theillusion of intelligence. They claim it willbe possible for machines to pass theTuring test without being able to doanything remotely like thinking at all – justlike chess computers can beat humanswithout thinking like a grandmaster. Afterall, just because a man passed himself offas a woman in the original game thatwouldn’t mean he was a woman.

There is in fact a competition run everyyear based on the Turing Test. TheLoebner Prize for artificial intelligence willaward $100,000 and a Gold Medal forthe first computer “whose responses areindistinguishable from a human's”. Manyof the entrants each year are created bypeople with no intention of buildingintelligent machines: just ones able topass the test. Just like studentssometimes “learn to a test” which theythen pass without gaining any realunderstanding of the subject, so it isargued chatbots will eventually win theLoebner prize without any understandingof what they are talking about. So far nochatbot has come close to winning theprize though – so maybe it’s a difficultillusion to pull off after all.

Intelligence TestingParty Games

Party games are just for fun– nothing serious aboutthem at all. A party gamecertainly wouldn't be behindone of the most importantresearch papers of thetwentieth century would it?Err, actually yes. A Victorian parlour gamecalled the Imitation Game lies at the heartof research on Artificial Intelligence and thequest to make machines think.

Back in the 1940s and 1950s, Alan Turing,one of the most influential computerscientists ever, was interested in givingcomputers intelligence. Intelligence is atricky thing though that is very hard to tiedown even in humans, never mind animalsor computers. Turing started to wonder ifever a computer deserved to be calledintelligent, how could we test it? He turnedto the Imitation Game for inspiration.

The Imitation Game involves two people, aman and a woman, both trying to convincethe rest of the party that they are thewoman. They go into a different room andare asked questions. Their answers areread out by a neutral referee. The womanmust answer truthfully. The man answers inany way he believes will convince everyoneelse he is really the woman.

The Imitation game tests for femaleness,but a similar test could be used to test forother things too, and in particular, Turingsuggested it could be used as a test forintelligence in a machine. If on questioninga hidden machine at length it can convinceyou that it is a person, then given youaccept that a person is intelligent, thecomputer must be too. Turing’s version ofthe imitation game therefore, replaced theman by a computer and the aim of bothperson and computer was to convinceeveryone that they were the human and so intelligent.

The paper helped launch the field ofArtificial Intelligence (AI). It pulls togetherbiologists, computer scientists andpsychologists in a quest to understand andreplicate intelligence. Turing thoughtmachines would pass his test before thetwentieth century was out, but Intelligencehas proved more elusive than that. AItechniques have delivered some stunningresults though – computers that can beatthe best human at chess, diagnose disease,and invest in stocks more successfully thanhumans, for example. Not bad for aVictorian parlour game.

So next time you find yourself playing agame of Musical Chairs, don't just sit onyour backside. Do some serious thinkingabout it and you too might launch a newresearch area.



The sweetnessillusion

The way we perceive the sweetness ofsugar depends on its temperature. So trythis. Take some sugar and water and mix ina bowl, then pour half the liquid into oneglass and pop this glass in the fridge tocool. Take the remainder and pour it intoanother glass and leave it near a radiator towarm up. The science says that theperceived sweetness of sucrose (sugar)increase by 40 per cent as the temperatureincreases from 4°C (about fridgetemperature) to 36°C (about bodytemperature). Take the two glasses of liquidand ask a friend which tastes sweeter (of course they both have the same amount of sugar in them). If your friendsays the warm glass is sweeter then youhave your illusion.

If you want to be really scientific about it,make more liquid in the bowl and put itequally into four glasses. Put one in thefridge, one by the radiator and leave theother two in the room. The two in the roomare called the experimental control. Askyour friend first to taste the sweetness ofthe two room temperature glasses. Becausethey have the same amount of sugar andthe same temperature they should taste thesame sweetness, so our control will showthat it is in fact the temperature that’scausing the effect and not, for example,that the first glass drunk always tastessweeter.

It’s also a good idea to have your friendswoosh their mouth out with normal waterbetween tastes of the sugary water so youdon’t contaminate your samples.

Your adaptablesenses: Lookingat your eyes’wiring

Scientists often work out a theory in onearea and find it also applies in another. Oursenses are a good example of this. They allhave the same sorts of characteristics andadaptation is one of the ones that iscommon across the senses.

In vision, for example, it’s been shown thatif you use special contact lenses that causean image to fall on exactly the same part ofthe retina (the light sensitive part at theback of your eye) as you move your eye, thatimage will vanish. The light sensitive cellsin the retina adapt to the image on them. In effect it’s there for too long and thevision system ends up ignoring it, waitingfor something interesting to come along.That is why your eyes make thousands oftiny involuntary movements called saccadesevery second, so that the image on theretina is always changing. This kind of eyemovement can also be used in computervision systems to help improve theiraccuracy, by building up the informationneeded to recognise objects, for example.

Perhaps one of the most “Gee, I’m abiological machine,” moments you couldhave is when you see your wiring. The retinaneeds lots of energy to measure the light inyour eye. To do this it needs blood, biology’sway of carrying nutrients. The surface ofyour retina is covered with a web of bloodcapillaries, but you don’t see them. Why?Because they are static on your retina, soyour visual system adapts them away. Fromtime to time, when you wake up and theearly morning sunlight comes in at an angleyou can briefly see a dense tree of thesecapillaries, as the light at an angle casts ashadow that the visual system wasn’texpecting and didn’t adapt to. If you’re verycareful you can use a torch (do not ofcourse use anything powerful that coulddamage your eyes – no laser pointers!) at anangle to create this effect. When you get itright it’s amazing. You can see the wiring onyour retina, albeit briefly. It’s quite asensational experience.

Here is a try-it-at-homeBlue Peter type guide to some easy-to-doillusions with yoursenses and other bodybits. It uses things youcan find around yourhome or school, and we guarantee no needfor any sticky-backedplastic.

Making sense of your senses

We have five senses: hearing, smell,taste, touch and vision. It’s your senses’job to let you know what’s happening inthe environment around you. We candistinguish millions of shades of colours,ten thousand different smells, we canfeel a feather touch our skin or hear afaint rustle of a leaf. Our senses arefantastic. Having to process all thatinformation in real time means that yourbrain is taking some short cuts in thecalculations though. It’s makingassumptions all along, and when thoseassumptions don’t apply then illusionshappen!

Sensational – the try ‘em at home guide to illusions




The floating arms illusionAdaptation also happens in your muscles,and can cause some strange effects. Standin a doorway and press the back of eachhand hard against the doorframe for aminute or so. Then walk forward. Your armswill feel like they want to float up. In factthey might actually do it. The reason is thatall the muscles in your body work in pairs.These are called antagonistic pairs and theyare needed as muscle fibre can onlycontract. You need one muscle on one sideof a joint to pull the bone one way andanother muscle on the other side to pull itback in the opposite direction. When youstand in the doorframe and push, you fatigueone of the sets of muscles. The muscleadapts to being under pressure. When youwalk forward the antagonistic muscle isready to go. It hasn’t had to adapt. The twosets are now out of balance so theantagonistic muscle starts to contract andup go your arms. Understanding how themuscles in the body work so cleverlytogether gives robot builders some cleverengineering models to hep them buildwalking machines.

The size-weight illusionThis illusion, first described over 100 years ago, shows that if you lift two objects of equal weight, you will tend toperceive the smaller object as heavier. You can test this out at home. Take two empty plastic bottles of differentsizes and, using scales, fill each with water or sand so they both weigh the same. Ask a friend to lift them up andask which they think is heavier. If they say the smaller bottle then the 'size-weight' illusion is at work. You can eventell them the objects are the same weight. The illusion will still persist.

But things get even stranger! Researchers have found that when people alternately lift objects of the same weightbut different size they apply the same fingertip force to both objects even though they still experience the size-weight illusion. One part of their brain is being fooled but another part of their brain isn’t, and the two parts aren’tcommunicating with each other.



Take three glasses of water, putone in the fridge, fill the otherwith warm water from the hottap (just warm NOT hot water)and fill the third with normalcold tap water.

Put the three glasses in a row in the order:warm, normal and cold. Pop a finger intothe warm water and, with your other hand,pop a finger in the fridge-cold water. Leavefor a short time, and then put both fingersinto the middle glass. You will feel that thefinger that was in the warm water feels coldand the finger originally in the fridge-coldwater now feels warm, even though theyare both now in the same temperaturewater. What’s happened here is that whenyour finger was, say, in the warm water itadapted to that temperature. Your body isreally only interested in things that changein the environment, as it is the changesthat you need to be able to react to. So,after your finger has adapted to the warmwater, when it goes into the middle glass it’s‘expecting’ it to be warm. When it’s not,your brain reasons, “this isn’t warm so itmust be cold”. Similarly, the finger in thefridge water adapts to coldness, and whenit moves into the centre glass, “that’s notcold, so it must be hot”. So one finger issaying hot, the other is saying cold, andboth are actually at the same temperature.

The TouchIllusionIf you raid a DIY toolbox you can try thesimilar sandpaper touch Illusion. Carefullyrub one hand on fine sandpaper, the otheron coarse sandpaper. Now take both handsand rub some medium sandpaper. It feelsdifferent to each hand. Why? Because thehand rubbing the fine sandpaper firstadapts to feeling fine roughness, whereasthe hand on the course sandpaper adaptsto lots of roughness. So like thetemperature illusion when your two handshave had their touch sensors adapted todifferent roughness, the medium paper willfeel different to each. Try to predict, fromthe Temperature Illusion explanation, whichhand will feel the medium paper as morerough, then try the experiment and see ifyou are right.

TheTemperatureIllusion


Here is an experimentthat looks at the power of the human mind tocontrol distant events.

ExperimentalEquipment required

• Deck of playing cards• Brain

Method

Get a deck of cards and give them a goodshuffle. Spread the cards on the tableface down. Now think of the colour REDand select any eight cards, then think ofthe colour BLACK and select another sevencards at random. Now think of RED again,select another six random cards, thenfinally BLACK again and select five cards.

Shuffle the cards you chose, and thenturn the pile face-up. Take the remainingcards, shuffle them and spread themface-down.

Now Concentrate

Now the remote control starts.Concentrate. You are going to separate thecards you selected (and that are now inyour face-up pile) into two piles, a REDpile and a BLACK pile, in the followingway.

Go through your face-up cards one at atime. If the next card is RED put it in theRED pile. For each RED card you put inyour RED pile think RED and select arandom card from the face-down cards onthe table without looking at it. Put thisrandom card in a pile face-down in frontof your RED pile.

Similarly if the next card is a BLACK cardput it face up on your BLACK pile, thinkBLACK and select a random face downcard. Put this face-down card in a pile infront of your BLACK pile.

Go through this procedure until you runout of face-up cards.

The experiment so far

You now have the following: a RED pileand in front of that a pile containing thesame number of face-down cards youselected while thinking RED. You also havea BLACK pile in front of which is a pile ofrandom cards you selected while thinkingBLACK.

Did your thoughtcontrol work?

Interestingly your thoughts haveinfluenced your choice of random cards!Don't believe me? Look at the pile ofrandom cards you chose and put in frontof your RED pile. Count the number of REDcards in this pile. Now look at the randomcards in front of your BLACK pile, andcount the number of BLACK cards youselected. They are the same! You selectedthe same number of RED and BLACK cardstotally at random!

It's a final proof that your sub-consciencemind can make you choose random cardsto balance those numbers! ... Or is it? See Magazine+ in the webzine for anexplanation of what is REALLY going on!

The remote controlbrain experimentThe remote controlbrain experiment




cs4fn is supported by EPSRC and the BCS

Back (page) to reality

Microsoft, ARM and Intel provide support for printing.

Visit the Perception Deception Stall at the Royal Society 2007 Summer Exhibition2-5 July

The Wake Up! Fix it! Web pages were developedfor Science Week 2007 with funding from RCUK

This issue has been about illusions andreality, so it’s only right to finish with someword tricks. Understanding how we turn thewritten word into understanding is a realchallenge for computer scientists. Get it rightand you can build computers that understandthe writing, a really useful thing to do. Firstoff when we look at a written sentence thereare two parts to it, the syntax and thesemantics.

A word spell

Syntax is about the structure of language –what is allowed to follow what, ignoringwhat it means. Turns out the order ofletters matters very little to humans. Howdo we read words? Do we pay attention toevery single letter to be able to extract theinformation? Perhaps not! Perhaps werecognise words and give them meaningwith a lot less information. Try and readthe paragraph below.

‘Aoccdrnig to rscheearch, it deosn't mttaerin waht oredr the ltteers in a wrod are, theolny iprmoetnt tihng is taht the frist andlsat ltteer be at the rghit pclae. The rsetcan be a toatl mses and you can sitll raedit wouthit porbelm. Tihs is bcuseae thehuamn mnid deos not raed ervey lteter byistlef, but the wrod as a wlohe’

We humans can get the gist of it eventhough the data is very messy, but imaginehow a poor computer would do, trying tomatch each letter to a set of stored words.The typos would floor it! So that’s whyexamining how humans read andunderstand is an important area ofresearch.

The trick is: Perfect the start and finish

Its not what you sayit’s the way that yousay it

Semantics is trickier. It’s about themeaning of words. Put the stress when youspeak a sentence in a different place andyou can change the reality!

‘I didn’t steal Granny’s chocolate cake’ –Wasn’t me, was someone else!

‘I didn’t steal Granny’s chocolate cake’ – It really wasn’t me!

‘I didn’t steal Granny’s chocolate cake’ – I planed to give it back, honest!

‘I didn’t steal Granny’s chocolate cake ’– It was actually Uncle John’s I stole!

‘I didn’t steal Granny’s chocolate cake’ – It was her vanilla sponge cake I nicked!

‘I didn’t steal Granny’s chocolate cake’ – It was her bar of chocolate!

How does a computer work that out fromthe words alone?

The trick is: say it like you mean it

The computer isbetter than you! (well sometimes)

Quickly count the number of letter ‘F’s in the following:

FINISHED FILES ARE THE RESULTOF YEARS OF SCIENTIFIC STUDYCOMBINED WITH THEEXPERIENCE OF YEARS

How many did you get? Three or four? Infact there are six F’s. During a quick read,your eyes and brain fix on the meaningful(lexical) words, and tend to ignore thegrammatical syntactic words (like the three‘of’s). Young children aged six tend not tomake this mistake. They take each word inturn slowly so can count the number of‘F’’s correctly, as would a current computerprogram. When you get older your brainstarts to learn to take shortcuts in readingto make it more fluid.

The trick is: fast and fluid usually gets you there

Colouring yourperception

Say the colour of the following words outloud quickly

Blue Red Green Yellow Red

Yellow Green Blue Yellow Red

Red Blue Yellow Red Green

Blue Yellow Red Green Green

I bet you read the word rather than thecolour! This is a really powerful illusioncalled the Stroop effect, named after itsdiscoverer John Ridley Stroop in 1935. He found that if you have to say coloursquickly then Green will normally cause lessof an error than Green, as the word and it’scolour are conflicting information that yourbrain can’t cope with. It shows again thatyour brain uses shortcuts to deal with allthe information you’re throwing at it. It makes assumptions and when thoseassumptions are wrong, your brain makes a mistake and an illusion happens.

The trick is: don’t always trust your brain

Studying how the brain makes mistakesgive us a valuable insight into how itworks, and since most of the time it doesa really good job of things, buildingcomputers that follow the same processes,even if they suffer the same illusions, is avery useful thing to do.

cs4fn is produced by Paul Curzonand Peter McOwan of theDepartment of Computer Science,Queen Mary, University of London.Support provided by Sue White.

You can trustyour brain most

of the time, but when itsassumptions

are wrong,illusions

follow…


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The Perception Deception - cs4fn: · PDF fileComputer Science for Fun Issue 5 Special Issue on The Perception Deception Computer Science Illusions Special Issue on Computer Science