Title :
Video Abstraction Based on Relational Graphs
Author :
Zhai, Su-Lan ; Luo, Bin ; Tang, Jin ; Zhang, Chun-yan
Author_Institution :
Anhui Univ., Hefei
Abstract :
Video abstraction plays an important role in video browsing, video indexing, video retrieval and other video applications. In the paper, an automatic video abstraction method is developed based on relational graph representations. Firstly, a relational graph is constructed for all the frames in a video sequence. Secondly, the graph is partitioned into different connected subgraphs. Thirdly, Isomap is performed to reduce the dimensionality of the data set, and the output of Isomap is used as feature vector of the video frames. Lastly, a mixture model with model selection is introduced to generate the fine grain video abstraction with the centre of each clustering as the keyframes. Experiments are conducted on real world video sets with satisfying video abstraction results.
Keywords :
abstracting; graph theory; image sequences; vectors; video signal processing; Isomap; connected subgraphs; dimensionality reduction; feature vector; graph partitioning; mixture model; model selection; relational graph representations; video abstraction; video browsing; video indexing; video retrieval; video sequence; Bandwidth; Clustering methods; Content based retrieval; Graphics; Image retrieval; Indexing; Video sequences; Video sharing; Video signal processing; Videoconference; Isomap; Video abstraction; manifold; mixture model;
Conference_Titel :
Image and Graphics, 2007. ICIG 2007. Fourth International Conference on
Conference_Location :
Sichuan
Print_ISBN :
0-7695-2929-1
DOI :
10.1109/ICIG.2007.177