Automatic extraction of important objects for an MPEG-7 compliant video database system
2008 IEEE 16th Signal Processing, Communication and Applications Conference, SIU
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We describe a method to automatically extract video objects, which are important for object-based indexing of videos in an MPEG-7 compliant video database system. Most of the existing salient object detection approaches detect visually conspicuous image structures, while our method aims to find regions that may be important for indexing in a video database system. Our method works on a shot basis. We first segment each frame to obtain homogeneous regions in terms of color and texture. Then, we extract a set of local and global color, shape, texture and motion features for each region. Finally, the regions are classified as being salient or non-salient using SVMs trained on a few hundreds of example regions. Experimental results from news video segments show that the proposed method is more effective in extracting the important regions in terms of human visual perception. ©2008 IEEE.
Human visual perceptions
Salient object detections
Video database systems
Indexing (of information)
Motion Picture Experts Group standards
Permalink (Please cite this version)http://hdl.handle.net/11693/26840
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