Foveated Figure-Ground Segmentation and Its Role in Recognition | Zendy

Mårten Björkman | Zendy; JanOlof Eklundh | Zendy

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Foveated Figure-Ground Segmentation and Its Role in Recognition

Author(s) -

Mårten Björkman,

JanOlof Eklundh

Publication year - 2005

Publication title -

kth publication database diva (kth royal institute of technology)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.5244/c.19.84

Subject(s) - segmentation , artificial intelligence , computer science , computer vision , image segmentation , scale space segmentation , context (archaeology) , segmentation based object categorization , prior probability , cognitive neuroscience of visual object recognition , pattern recognition (psychology) , feature extraction , geography , bayesian probability , archaeology

Figure-ground segmentation and recognition are two interrelated processes. In this paper we present a method for foveated segmentation and evaluate it in the context of a binocular real-time recognition system. Segmentation is solved as a binary labeling problem using priors derived from the results ofa simplistic disparity method. Doing so we are able to cope with situations when the disparity range is very wide, situations that has rarely been considered, but appear frequently for narrow-field camera sets. Segmentation and recognition are then integrated into a system able to locate, attend to and recognise objects in typical cluttered indoor scenes. Finally, we try to answer two questions: is recognition really helped by segmentation and what is the benefit of multiple cues for recognition?

QC 20120111

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