15 November 2011 Categorizing video shots by utilizing SVM and wavelet
Author Affiliations +
Proceedings Volume 8335, 2012 International Workshop on Image Processing and Optical Engineering; 83351A (2011) https://doi.org/10.1117/12.917663
Event: 2012 International Workshop on Image Processing and Optical Engineering, 2012, Harbin, China
Abstract
Shots classification plays an important role in well indexing, browsing and retrieving video content. By that, the large amount of video content can be efficiently indexed, and then, it can provide convenience for managing video. In this paper, edge features are firstly extracted by wavelet, which can not only reduce amount of shots data but also preserve the important structural properties of shots. And then, to reflect local properties of shots, ratio of edge pixels in each sub-window is calculated. After that, color moments are computed to reduce loss of global properties, which can assist edge features in well indexing shots. Finally, support vector machine (SVM), which has a very good performance on pattern recognition, is employed to classify shots. Experimental results demonstrate that this method can efficiently categorize video shots and satisfy the basic needs of shots classification.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Haina Jiang, Haina Jiang, Xiquan Xia, Xiquan Xia, } "Categorizing video shots by utilizing SVM and wavelet", Proc. SPIE 8335, 2012 International Workshop on Image Processing and Optical Engineering, 83351A (15 November 2011); doi: 10.1117/12.917663; https://doi.org/10.1117/12.917663
PROCEEDINGS
7 PAGES


SHARE
Back to Top