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Graph-based video fingerprinting using double optimal projection
Affiliation:1. School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan 250014, China;2. School of Information Science and Engineering, Shandong University, Jinan 250100, China;3. Department of Computer Science, University of Missouri, Columbia, MO 65211, United States;1. Center for Microscopy – Microanalysis and Information Processing, University “Politehnica” of Bucharest, 313 Splaiul Independentei, Sect. 6, 060042 Bucharest, Romania;2. Light Microscopy and Screening Center, Swiss Federal Institute of Technology ETH Zurich, Schaffmatstrasse 18, Zurich, Switzerland;3. Electrical Engineering Department, Valahia University Targoviste, Bd. Carol I, Nr. 2, Romania;1. Department of Electrical Engineering, University of Washington, Seattle, WA, United States;2. Industrial Technology Research Institute (ITRI), Taiwan;3. IBM T.J. Watson Research Center, Hawthorne, NY, United States;1. Department of Computer Engineering, Bilkent University, 06800 Ankara, Turkey;2. Department of Computer Engineering, Hacettepe University, 06800 Ankara, Turkey;1. Department of Information Management, Junior College of Medicine, Nursing and Management, I-Lan, Taiwan;2. Department of Electronic Engineering, National I-Lan University, I-Lan, Taiwan;1. Institute of Computing, University of Campinas, Campinas, SP 13083-852, Brazil;2. Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, MG 31270-010, Brazil;1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China;2. State Key Lab. of Computer Science, Inst. of Software, Chinese Academy of Sciences, Beijing, China;3. Dept. of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macao, China
Abstract:A double optimal projection method that involves projections for intra-cluster and inter-cluster dimensionality reduction are proposed for video fingerprinting. The video is initially set as a graph with frames as its vertices in a high-dimensional space. A similarity measure that can compute the weights of the edges is then proposed. Subsequently, the video frames are partitioned into different clusters based on the graph model. Double optimal projection is used to explore the optimal mapping points in a low-dimensional space to reduce the video dimensions. The statistics and geometrical fingerprints are generated to determine whether a query video is copied from one of the videos in the database. During matching, the video can be roughly matched by utilizing the statistics fingerprint. Further matching is thereafter performed in the corresponding group using geometrical fingerprints. Experimental results show the good performance of the proposed video fingerprinting method in robustness and discrimination.
Keywords:Video copy detection  Content protection  Video fingerprinting  Dimensionality reduction  Double optimal projection  Graph model  Intra-cluster  Inter-cluster
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