期刊名称：Journal of Advanced Computer Science & Technology
印刷版ISSN：2227-4332
电子版ISSN：2227-4332
出版年度：2016
卷号：5
期号：1
页码：1-7
DOI：10.14419/jacst.v5i1.4035
出版社：Science Publishing Corporation
摘要：Video often include frames that are irrelevant to the scenes for recording. These are mainly due to imperfect shooting, abrupt movements of camera, or unintended switching of scenes. The irrelevant frames should be removed before the semantic analysis of video scene is performed for video retrieval. An unsupervised approach for automatic removal of irrelevant frames is proposed in this paper. A novel log-spectral representation of color video frames based on Fibonacci lattice-quantization has been developed for better description of the global structures of video contents to measure similarity of video frames. Hyperclique pattern analysis, used to detect redundant data in textual analysis, is extended to extract relevant frame clusters in color videos. A new strategy using the k-nearest neighbor algorithm is developed for generating a video frame support measure and an h-confidence measure on this hyperclique pattern based analysis method. Evaluation of the proposed irrelevant video frame removal algorithm reveals promising results for datasets with irrelevant frames.
关键词：Content-Based Video Retrieval;Fibonacci Lattice;Hyperclique Pattern;Irrelevant Removal;Log Spectrum.
