Semantic video object extraction based on backward tracking of multivalued watershed
Daniel Gática-Pérez, Ming–Ting Sun, Chuang Gu · 1999
We present a novel algorithm for semantic video object (SVO) extraction, based on a new multivalued morphological spatial segmentation that integrates color and edge information, and object tracking by backward region classification. Our proposed spatial segmentation incorporates a new marker extraction method based on intensity edge information that improves the definition of the real borders of the scene objects, and a new distance criterion based on color and edge information to guide the watershed algorithm. Experimental results on several MPEG-4 test video sequences show that our algorithm improves the precision of the extracted SVO boundaries compared to the traditional water-shed technique, and that it is capable of tracking multiple SVOs in static and moving camera scenarios.