文章基本信息

标题：A Fast Search Algorithm for Large Video Database Using HOG Based Features
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作者：Qiu Chen ; Koji Kotani ; Feifei Lee 等
期刊名称：Computer Science & Information Technology
电子版ISSN：2231-5403
出版年度：2016
卷号：6
期号：3
页码：35-41
DOI：10.5121/csit.2016.60304
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：In this paper, we propose a novel fast video search algorithm for large video database.Histogram of Oriented Gradients (HOG) has been reported which can be reliably applied toobject detection, especially pedestrian detection. We use HOG based features as a featurevector of a frame image in this study. Combined with active search, a temporal pruningalgorithm, fast and robust video search can be achieved. The proposed search algorithm hasbeen evaluated by 6 hours of video to search for given 200 video clips which each length is 15seconds. Experimental results show the proposed algorithm can detect the similar video clipmore accurately and robust against Gaussian noise than conventional fast video searchalgorithm.
关键词：Fast search; Video database; HOG Features