Im currently working on the third tutorial in my
computer vision tutorial series, so what better time than to offer a supplementary?
A lecture on facial recognition:
http://mitworld.mit.edu/video/154/(1 hour)
"He theorizes that facial perception is a holistic process: we broadly take in the relationship, for instance, of eyes, nose and mouth. He tested this hypothesis by creating a computer program that could similarly grasp facial structure, and the program was able to “see” a face within a larger picture. In his Hirschfeld Project, Sinha is trying to distill the caricaturists’ understanding about the important landmarks of a face."
Key Points- Vision is our most important sensor.
- Facial recognition will greatly enhance AI on mobile robots.
- "Parallel and Hierarchical Model of Vision Processing" - dividing up different vision tasks as entirely seperate
- edge detector neurons
- action potentials, signals from neurons, tuned to seeing different things
- object recognition, very fundamental problem in neuroscience
- over 1200 studies done in facial recognition in the last two decades
- image quality is important for facial recognition
- spatial configuration important (location of eyes, nose, mouth, etc.)
- facial recognition reaction time increases with lower quality images
- removing facial image degradation based on training techniques
- which aspects of facial recognition are important, and which are not?
- characterture artists 'understand facial recognition intuitively'
- facial recognition and object recognition are very similar tasks
- how does the mind collect and store object recognition information?
