A robust shot transition detection method based on support vector machine in compressed domain-Reference-Cited by-同舟云学术

A robust shot transition detection method based on support vector machine in compressed domain

Published:2007-09 Issue:12 Volume:28 Page:1534-1540
ISSN:0167-8655
Container-title:Pattern Recognition Letters
language:en
Short-container-title:Pattern Recognition Letters

Author:

Cao Jianrong,Cai Anni

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference21 articles.

1. A unified model for techniques on video-shot transition detection;Bescos;IEEE Trans. Mutimedia,2005

2. Foveated shot detection for video segmentation;Boccignone;IEEE Trans. Circ. Systems Video Technology,2005

3. A Tutorial on Support Vector Machines for Pattern Recognition;Burges,1998

4. Chang, C.C., Lin, C.J., 2001. LIBSVM: A library for support vector machine. Software available from: .

5. Feng, J., Lo, K.-T., Mehrpour, H., 1996. Scene change detection algorithm for MPEG video sequence. In: Proc. IEEE Internat. Conf. Image Processing. Lausanne, Switzerland, pp. 821–824.

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