Key frames extraction based on optical-flow and mutual information entropy

doi:10.1088/1742-6596/1646/1/012112

	Key frames extraction based on optical-flow and mutual information entropy
	Bao, Guangbin; Li, Dongfang; Mei, Yuli
	2020-10-30
会议日期	August 14, 2020 - August 15, 2020
会议地点	Guiyang, China
关键词	Computer networks Extraction Indexing (of information) Information systems Information use Video recordingFlow charac-teristics Key-frame extraction Minimum mutual informations Mutual informations Optical flow methods Threshold-value Video retrieval Video summaries
卷号	1646
期号	1
DOI	10.1088/1742-6596/1646/1/012112
英文摘要	Key frames provide a suitable video summary and framework for video indexing, browsing and retrieval, and how to extract key frames is the core in the field of video retrieval. In order to solve the problem of redundancy and missing selection in key frame extraction, this paper proposed a key frame extraction algorithm based on optical flow and mutual information entropy. This algorithm integrates mutual information entropy and optical flow characteristics to extract key frames. First, the optical flow method calculated the total optical flow of each frame of the image, and selected the video frame with extreme optical flow difference in the neighbourhood as the key frame, and the other video frames were put into the candidate key frame set; by calculating the mutual information entropy of the key frame set, the minimum mutual information entropy is taken as the threshold; Then, The mutual information entropy of the candidate key frame set was calculated, and the image frames larger than the threshold value were put into the key frame set; Finally, redundant key frames are deleted through the measurement of inter-frame similarity, and the remaining key frames are the key frames to be extracted. The experimental results show that compared with other methods, the accuracy of extracted key frames by this approach is significantly improved on precision, recall and F-score, and the extracted key frames can reflect video content more effectively. © 2020 Journal of Physics: Conference Series.
会议录	Journal of Physics: Conference Series
会议录出版者	IOP Publishing Ltd
语种	英语
ISSN号	17426588
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/132614]
专题	网络与信息中心
作者单位	School of Computer and Communication, Lanzhou University of Technology, Lanzhou; 730050, China
推荐引用方式 GB/T 7714	Bao, Guangbin,Li, Dongfang,Mei, Yuli. Key frames extraction based on optical-flow and mutual information entropy[C]. 见:. Guiyang, China. August 14, 2020 - August 15, 2020.