Title :
Motion Histogram Analysis Based Key Frame Extraction for Human Action/Activity Representation
Author :
Shao, Ling ; Ji, Ling
Author_Institution :
Philips Res. Eur., Eindhoven, Netherlands
Abstract :
Key frame extraction is an important technique in video summarization, browsing, searching, and understanding. In this paper, a novel algorithm for key frame extraction based on intra-frame and inter-frame motion histogram analysis is proposed. The extracted key frames contain complex motion and are salient in respect to their neighboring frames, and can be used to represent actions and activities in video. The key frames are first initialized by finding peaks in the curve of entropy calculated on motion histograms in each video frame. The peaked entropies are then weighted by inter-frame saliency which we use histogram intersection to output final key frames. The effectiveness of the proposed method is validated by a large variety of real-life videos.
Keywords :
feature extraction; image motion analysis; video signal processing; human action representation; human activity representation; interframe motion histogram analysis; interframe saliency; intraframe motion histogram analysis; key frame extraction; Algorithm design and analysis; Content based retrieval; Data mining; Entropy; Histograms; Humans; Image motion analysis; Indexing; Motion analysis; Video sequences; Key frame extraction; action recognition.; entropy; histogram intersection; motion histogram; optical flow;
Conference_Titel :
Computer and Robot Vision, 2009. CRV '09. Canadian Conference on
Conference_Location :
Kelowna, BC
Print_ISBN :
978-0-7695-3651-4
DOI :
10.1109/CRV.2009.36