Friday, August 31, 2012

AI vs perception vs vision

So far I was never very sure of how Artificial Intelligence, Machine Perception, and Computer Vision are exactly related. I am still not sure ( though I can probably guess) whether/how computer vision, machine vision and robot vision are really different, or exactly the same.
Following is an excerpt from the Book [1]:

"... We propose the following by no means universally accepted definition of AI. AI is the study of how to make computers do things which, at the moment, people do better. This definition is, of course, somewhat ephemeral because of its reference to the current state of computer sciences. And it fails to include some areas of potentially very large impact, namely the problems that cannot now be solved well by either computers or people.
Perception involves interpreting sights, sounds, smells, and touch. Action includes the ability to navigate through the world and manipulate objects. In robotics these processes are important. Most of AI is concerned only with cognition. But problems in perception and action are substantial in their own right and are being tackled by researchers in the field of robotics.
In the past, robotics and AI have been largely independent endeavors, and they have developed different techniques to solve different problems. We should note down one key difference between AI programs and robots: While AI programs usually operate in computer-simulated worlds, robots must operate in the physical world. As an example, consider making a move in chess. An AI program can search millions of nodes in a game tree without ever having to sense or touch anything in the real world. A complete chess-playing robot, on the other hand,must be capable of grasping pieces, visually interpreting board positions, and carrying on a host of other actions." 

Wednesday, February 9, 2011

Quick questions

Given an arbitrary 3x3 matrix, how do you know it's a homography?

Given an arbitrary 3x3 matrix, how do you know it's an affine transformation?

Given an arbitrary 3x3 matrix, how do you know it's an Euclidean transformation?

1) Should be invertible.
2) Should be invertible and last row should be (0,0,1).
3) Should be invertible and last row should be (0,0,1) and upper-left 2x2 matrix should be orthogonal.

How do you know it's invertible?

How do you know the upper-left 2x2 matrix is orthogonal?

1) determinant should be zero.
2) That means its columns ( & hence rows too) should be orthonormal. Check their dot product.