Title :
Video Break Detection based on Similarity Analysis and Temporal Statistical Characteristics
Author_Institution :
Sch. of Math. & Comput. Sci., Fuzhou Univ., Fujian
Abstract :
Video shot boundary detection is a fundamental task in any kind of video content manipulation and retrieval. The area of shot boundary detection has been extensively studied, but achieving highly accurate detection results remains a challenge. In this paper, we present a novel algorithm for video cut detection. The algorithm is implemented and evaluated on the TRECVID benchmark platform. The experimental results show the effectiveness of the proposed approach. The algorithm provides a clue to the gradual transition detection
Keywords :
benchmark testing; object detection; statistical analysis; video retrieval; video signal processing; TRECVID benchmark; shot boundary detection; similarity analysis; temporal statistical characteristic; video break detection; video content manipulation; video retrieval; Computer science; Content based retrieval; Detection algorithms; Filtering; Gunshot detection systems; Histograms; Intelligent systems; Laboratories; Mathematics; Testing;
Conference_Titel :
Multimedia and Expo, 2006 IEEE International Conference on
Conference_Location :
Toronto, Ont.
Print_ISBN :
1-4244-0366-7
Electronic_ISBN :
1-4244-0367-7
DOI :
10.1109/ICME.2006.262907
