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Hierarchical Color Segmentation for Region-Based Visual Attention
Date: 2012/06/06
Time: 16:30 h
Place: P1.4.17
Author(s): Yuan Gao, GET Lab

Am Mittwoch, den 06. Juni 2012, hält Yuan Gao um 16:30 Uhr im Raum P 1.4.17 einen Vortrag über seine Bachelorarbeit mit dem Titel:

Hierarchical Color Segmentation for Region-Based Visual Attention


In control of mobile robots, computer vision plays an important role. The current saliency detecting approach used in GET Lab performs color-segmentation as an initial step and then determines saliency using region lists. This work extends the existing implementation by enabling support for hierarchical region-based segmentation. The input image is segmented in different levels. At first the image is segmented into a few regions with coarse granularity. In the next step each region produced is segmented in a finer granularity, so that the big regions are split into smaller ones. The process continues until a predefined level is reached, while all the parent-child (region-subregion) relations are stored as a region-tree. Experiments are conducted to test this approach applied to attention-related problems: Time pressure is simulated by limiting processing to certain levels; Fast scene classification based on the "Gist" obtained from low grain regions; and extracting objects by backtracking from salient subregions to parent regions.