Title :
Enhancing the MST-CSS Representation Using Robust Geometric Features, for Efficient Content Based Video Retrieval (CBVR)
Author :
Chattopadhyay, Chiranjoy ; Das, S.
Author_Institution :
Dept. of Comput. Sci. & Eng., Indian Inst. of Technol., Madras, Chennai, India
Abstract :
Multi-Spectro-Temporal Curvature Scale Space (MST-CSS) had been proposed as a video content descriptor in an earlier work, where the peak and saddle points were used for feature points. But these are inadequate to capture the salient features of the MST-CSS surface, producing poor retrieval results. To overcome these, we propose EMST-CSS (Enhanced MST-CSS) as a better feature representation with an improved matching method for CBVR (Content Based Video Retrieval). Comparative study with the existing MST-CSS representation and two state-of-the-art methods for CBVR shows enhanced performance on one synthetic and two real-world datasets.
Keywords :
content-based retrieval; feature extraction; pattern matching; video retrieval; video signal processing; CBVR; Enhanced MST-CSS; MST-CSS representation; MST-CSS surface; content based video retrieval; feature points; feature representation; matching method; multispectro-temporal curvature scale space; robust geometric features; saddle points; salient features; video content descriptor; Cameras; Feature extraction; Humans; Robustness; Shape; Surface treatment; Trajectory; CBVR; Curvature; EMST-CSS; Matching; Peak; Precision-Recall; Ridge; STV; VOB;
Conference_Titel :
Multimedia (ISM), 2012 IEEE International Symposium on
Conference_Location :
Irvine, CA
Print_ISBN :
978-1-4673-4370-1
DOI :
10.1109/ISM.2012.71