| ECVision indexed and annotated bibliography of cognitive computer vision publications This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1 The complete text version of this BibTeX file is available here: ECVision_bibliography.bib
S. R. Schwartz and B. W. Wah
ABSTRACT
Both human vision and human learning are far from fully understood, yet machine imitation of these abilities has proven very useful. Research up to now has made much progress in tracing the desired result backward to the algorithms that implement it. For example, we know how or what we want the machine to perform, but lacking a complete understanding of the biological processes, we proceed to find an algorithmic solution. In both the fields of machine leaning and computer vision this has been the case. This chapter presents an approach to integrating machine learning techniques to improve the performance of computer vision algorithms. The topics considered here are the techniques for machine learning, examples of how they can be applied, and a specific case study detailing the application of the methods. Topics not considered here include reasoning about detected objects and planning interaction with the environment. |
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