Extension 3: Vision

A well-known anecdote relates how, sometime in 1966, the legendary Artificial Intelligence pioneer Marvin Minsky directed an undergraduate student to solve “the problem of computer vision” as a summer project (1). This anecdote is often resuscitated to illustrate how egregiously the difficulty of computational vision has been underestimated. Indeed, nearly forty years later, the discipline continues to confront numerous unsolved (and perhaps unsolvable) challenges, particularly with respect to high-level “image understanding” issues such as pattern recognition and feature recognition. Nevertheless, the intervening decades of research have yielded a great wealth of well-understood, low-level techniques that are able, under controlled circumstances, to extract meaningful information from a camera scene. These techniques are indeed elementary enough to be implemented by novice programmers at the undergraduate or even high-school level.