Contour-based classification of video objects
Stephan R. Richter, Gerald Kuehne, Oliver Schuster · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2001
The recognition of objects that appear in a video sequence is an essential aspect of any video content analysis system. We present an approach which classifies a segmented video object base don its appearance in successive video frames. The classification is performed by matching curvature features of the contours of these object views to a database containing preprocessed views of prototypical objects using a modified curvature scale space technique. By integrating the result of an umber of successive frames and by using the modified curvature scale space technique as an efficient representation of object contours, our approach enables the robust, tolerant and rapid object classification of video objects.