Title :
A new method for shot gradual transiton detection using support vector machine
Author :
Ling, Jian ; Lian, Yi-Qun ; Zhuang, Yue-ting
Author_Institution :
Inst. of Artificial Intelligence, Zhejiang Univ., China
Abstract :
The detection of gradual transition is much more difficult than that of abrupt transition. In this paper, a new method for gradual transition detection that applies support vector machine is proposed. First, an improved variance projection function is introduced, and its practicality to the detection of gradual transition is analyzed as well. Then by using this variance projection function, the distance between the video frames is defined, and a method to calculate the feature vector of changes of the distance is proposed. Finally, a statistical learning method based on the support vector machine is devised to determine whether the changes of the distance are caused by gradual transition or not. The experiments results show that this method has better detection resolution and less timing complexity, and thus satisfactorily meets the requirements of real-time video-shot detection.
Keywords :
feature extraction; learning (artificial intelligence); support vector machines; video signal processing; distance change feature vector; shot gradual transiton detection; statistical learning; support vector machine; variance projection function; video frames; video similarity; video-shot detection; Analysis of variance; Artificial intelligence; Cameras; Feature extraction; Gunshot detection systems; Layout; Statistical learning; Support vector machines; Timing; Video sequences; Variance projection function; gradual transition detection; support vector machine; video similarity;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527934