Abstract
With the development of multimedia technology and the explosive growth of video data, content-based video copy detection has attracted considerable attentions in the multimedia and the computer vision community. However, most video copy detection methods only focus on the contents of key frames and ignore their temporal context information. In this paper, we proposed to express the temporal context of key frame as binary codes, and compare the key frames' binary codes by calculating Hamming Distance to achieve temporal verification efficiently and implicitly. Experimental results on the publicly available video database (TRECVID 2009) indicate the proposed approach achieves high efficiency and accuracy.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
