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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?
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