Parallel guessing: A strategy for high-speed computation

摘要

Conventional approaches to speeding up image understanding computation involving conventional serial algorithms attempt to decompose these algorithms into portions that can be computed in parallel. Because many classes of algorithms do not readily decompose, one seeks some other basis for parallelism. In this paper we argue that “parallel guessing” for image analysis is a useful approach, and that several recent scene analysis algorithms are based on this concept. Problems suitable for this approach have the characteristic that either “distance” from a true solution, or the correctness of a guess, can be readily checked. We review image analysis algorithms that have a parallel guessing or randomness flavor.