Content-Based Video Search: Is there a Need, and Is it Possible?

There is a large and rapidly increasing amount of video data on the Internet and in personal or organizational collections. Fast and accurate video search emerges to be an important issue. The need and main technical challenges for video retrieval are similar to those for the content-based image retrieval (CBIR) problem. Lack of meaningful and comprehensive text annotation means that an approach based on content similarity can be promising; and the differences between an often high-level search intention and the low-level features used in content-based search techniques suggest that content-based video retrieval (CBVR) may also suffer from "semantic gap" issues. In this paper, we analyze the problem of CBVR from related work in the literature as well as some current work in our team, focusing on the relationship between CBIR and CBVR, open yet well-defined research issues and practical applications of CBVR.

[1]  Qi Tian,et al.  Fast and Robust Short Video Clip Search for Copy Detection , 2004, PCM.

[2]  Giridharan Iyengar,et al.  Distributional clustering for efficient content-based retrieval of images and video , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[3]  Deok-Hwan Kim,et al.  Similarity search for multidimensional data sequences , 2000, Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073).

[4]  Avideh Zakhor,et al.  Efficient video similarity measurement with video signature , 2002, Proceedings. International Conference on Image Processing.

[5]  Heng Tao Shen,et al.  Principal Component Analysis , 2009, Encyclopedia of Biometrics.

[6]  Eamonn J. Keogh,et al.  Exact indexing of dynamic time warping , 2002, Knowledge and Information Systems.

[7]  Kunio Kashino,et al.  A quick search method for audio and video signals based on histogram pruning , 2003, IEEE Trans. Multim..

[8]  Ruud M. Bolle,et al.  Comparison of sequence matching techniques for video copy detection , 2001, IS&T/SPIE Electronic Imaging.

[9]  Avideh Zakhor,et al.  Fast similarity search and clustering of video sequences on the world-wide-web , 2005, IEEE Transactions on Multimedia.

[10]  Chong-Wah Ngo,et al.  Practical elimination of near-duplicates from web video search , 2007, ACM Multimedia.

[11]  Zi Huang,et al.  Statistical summarization of content features for fast near-duplicate video detection , 2007, ACM Multimedia.

[12]  Zi Huang,et al.  UQLIPS: A Real-time Near-duplicate Video Clip Detection System , 2007, VLDB.

[13]  Joachim M. Buhmann,et al.  Empirical Evaluation of Dissimilarity Measures for Color and Texture , 2001, Comput. Vis. Image Underst..

[14]  Zi Huang,et al.  Online Near-Duplicate Video Clip Detection and Retrieval: An Accurate and Fast System , 2009, 2009 IEEE 25th International Conference on Data Engineering.

[15]  Xiao-Ping Zhang,et al.  Automatic identification of digital video based on shot-level sequence matching , 2005, MULTIMEDIA '05.

[16]  David A. Forsyth,et al.  Matching Words and Pictures , 2003, J. Mach. Learn. Res..

[17]  Heng Tao Shen,et al.  A New Similarity Measure for Near Duplicate Video Clip Detection , 2007, APWeb/WAIM.

[18]  Lei Chen,et al.  Robust and fast similarity search for moving object trajectories , 2005, SIGMOD '05.

[19]  Marcel Worring,et al.  Content-Based Image Retrieval at the End of the Early Years , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Sang Uk Lee,et al.  Efficient video indexing scheme for content-based retrieval , 1999, IEEE Trans. Circuits Syst. Video Technol..

[21]  Tat-Seng Chua,et al.  A match and tiling approach to content-based video retrieval , 2001, IEEE International Conference on Multimedia and Expo, 2001. ICME 2001..

[22]  Alberto Del Bimbo,et al.  Video Clip Matching Using MPEG-7 Descriptors and Edit Distance , 2006, CIVR.

[23]  Dimitrios Gunopulos,et al.  Discovering similar multidimensional trajectories , 2002, Proceedings 18th International Conference on Data Engineering.

[24]  Heng Tao Shen.  Video Sequence Indexing , 2009, Encyclopedia of Database Systems.

[25]  Justin Zobel,et al.  Detection of video sequences using compact signatures , 2006, TOIS.

[26]  Milind R. Naphade,et al.  Novel scheme for fast and efficent video sequence matching using compact signatures , 1999, Electronic Imaging.

[27]  Donald A. Adjeroh,et al.  A Distance Measure for Video Sequences , 1999, Comput. Vis. Image Underst..

[28]  James Ze Wang,et al.  Real-Time Computerized Annotation of Pictures , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[29]  Shih-Fu Chang,et al.  Survey of compressed-domain features used in audio-visual indexing and analysis , 2003, J. Vis. Commun. Image Represent..

[30]  B. Vasudev,et al.  Spatiotemporal sequence matching for efficient video copy detection , 2005, IEEE Transactions on Circuits and Systems for Video Technology.

[31]  Beng Chin Ooi,et al.  Towards effective indexing for very large video sequence database , 2005, SIGMOD '05.

[32]  Li Chen,et al.  Video copy detection: a comparative study , 2007, CIVR '07.

[33]  Marcel Worring,et al.  Multimodal Video Indexing : A Review of the State-ofthe-art , 2001 .

[34]  Chu-Song Chen,et al.  A Time Warping Based Approach for Video Copy Detection , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[35]  Nicu Sebe,et al.  Content-based multimedia information retrieval: State of the art and challenges , 2006, TOMCCAP.

[36]  James Ze Wang,et al.  Image retrieval: Ideas, influences, and trends of the new age , 2008, CSUR.