I came across a nice short article written by Shimon Edelman titled Constraints on the nature of the neural representation of the visual world. Shimon got his PhD from Weizmann Institute of Science in 1988 under the guidance of the infamous Prof. Shimon Ullman and is now a Professor of Psychology at Cornell. If you are a vision hacker -- a code-writing graphical-model advocating graduate student in computer science -- then you might ask yourself: Why should I care what psychologists/philosophers have to say about vision?
The problem is that overfitting to what is currently *hot* at CVPR isn't very productive if you want to solve big problems. Philosophers, psychologists, roboticists, and cognitive neuroscientists have a lot to say about vision and offer plenty of ideas as to what they expect to see in a successful vision system. While being a CS graduate student something like "the problem of computer vision" might seem like a rather grand goal; however, these other scientists (from different fields) suggest that it is unlikely that a pure CS approach will get the glory.
Some concepts that are brought up in this paper are the following: ontological strategy, context, inherent ambiguities in segmentation, ineffability of the visual world, multidimensional similarity space. I think looking at vision from a philosophical point of view is not only enlightening, but suggests that what we should be after is more than just solving the problem of computer vision. What does it mean to solve the problem of computer vision after all? What we should be after is a theory of intelligence -- a theory of mind -- and strive to build truly intelligent machines.