Objects

Floyd NelsonA.D. 2009 Dec 29

Examples of Objects

• Representation: desk– Object: brown, with four

brown lines branching off from it

• Representation: loud– Object: noise that is loud

• Representation: name– Object: qualities that

describe the name

• objects are usually pictures, but can involve 1 dimensional inputs and/or multiple inputs, outputs, etc.

• an object is a reference to a kind of experience

An Object’s Elements

• when describing a new object these qualities are used – pictures from views of

the object– average color– “rotation shift”

• when describing a current object these qualities are used – rotation– size– stretch– *rectangular

trapezoidal

Objects to Look for• Most objects do not disappear

(except for objects moving on computer screens, out of vision or behind a closer object).– So the system should check for

objects that were there previously.

• Rooms usually have the same items/objects in them.– So the system should check for

objects that are usually in the location that it is in.

– The system’s location can be found by:• knowing some of the objects in the

room• knowing what objects it saw before

it entered the room

• Objects may appear to turn into other objects.– A pencil looks like a long

yellow rectangular shape; after it is rotated, it can look like a small pink circle

• If an object is mentioned from communication, the system should probably search for that object.

• Anything that changes (moves)

Identifying Objects

• Use color difference to generate an outline of the object

• Find the longest point-to-point of the object

• Compare with other objects. If radically different from all other objects, make a new object.

• Use touch information to determine 3D shape

• There are several different kinds of objects for each word in human languages.– There is more than one

shape of computer screens and chairs.

– When someone thinks of a dog, they will not always think of the same dog, even if it is the same species of dog (one could be fatter).

Methods of Identifying Objects

• 1. To find the range of pixels to work with:

• 2. Find its longest side and its bisector using a line test of varying angles– The minimum (from side) and

maximum (from diagonal) are identified from the first test

• 3. Overlap the two images; the colors in fig. C continually alternates (green, red, green, red, …)• blue / (red + green + blue) = %

similar

Oddities 1

• Counting the number of members of a flock– Count each individual

while remembering which ones were counted

– Area × Average_Density = number_of_Members

Oddities 2

• Disappearing and appearing objects & rapid change of color– iguanas– glow in the dark– light bulbs– night/day– television– computer screens

oddities 3

• blur• fog• rainbow

• How can the perimeter of the object be determined?