Video Sequence Indexing
Video indexing; Video retrieval; Video search
A video is usually defined as a sequence of high-dimensional feature vectors. Video sequence indexing consists of describing the content of video sequences from a video database to allow effective and efficient search and retrieval. Given a query video sequence, video sequence indexing aims to find its similar video sequences from a video database quickly. Typically, it includes the following major components: effective summarization of the high-dimensional sequence, effective access method for indexing the obtained summarization, and efficient query processing method.
Video feature extraction and content analysis have been studied for several decades since the emergence of video data. Recently, video sequence indexing has attracted plenty of attention because of the huge amount of video data. With ever more heavy usage of video devices and advances in video processing technologies, the amount of...
- 3.Chen L, Özsu MT, Oria V. Robust and fast similarity search for moving object trajectories. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2005. p. 491–502.Google Scholar
- 5.Shen HT, Zhou X, Huang Z, Shao J. Statistical summarization of content features for fast near-duplicate video detection. In: Proceedings of the 15th ACM International Conference on Multimedia; 2007. p. 164–5.Google Scholar
- 6.Shen HT, Ooi BC, Zhou X, Huang Z. Towards effective indexing for very large video sequence database. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2005. p. 730–41.Google Scholar
- 7.Iyengar G, Lippman A. Distributional clustering for efficient content-based retrieval of images and video. In: Proceedings of the International Conference Image Processing; 2000. p. 81–4.Google Scholar
- 9.Lee J, Oh J-H, Hwang S. STRG-index: spatio-temporal region graph indexing for large video databases. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2005. p. 718–29.Google Scholar
- 11.Rasetic S, Sander J, Elding J, Nascimento MA. A trajectory splitting model for efficient spatio-temporal indexing. In: Proceedings of the 31st International Conference on Very Large Data Bases; 2005. p. 934–45.Google Scholar
- 12.Pfoser D, Jensen CS, Theodoridis Y. Novel approaches in query processing for moving object trajectories. In: Proceedings of the 26th International Conference on Very Large Data Bases; 2000. p. 395–406.Google Scholar
- 13.Song J, Yang Y, Huang Z, Shen HT, Hong R. Multiple feature hashing for real-time large scale near-duplicate video retrieval. In: Proceedings of the 19th ACM International Conference on Multimedia; 2011. p. 423–32.Google Scholar
- 14.Zhu X, Huang Z, Shen HT, Zhao X. Linear cross-modal hashing for efficient multimedia search. In: Proceedings of the 21st ACM International Conference on Multimedia; 2013. p. 143–52.Google Scholar
- 15.TRECVID. 2007. http://www-nlpir.nist.gov/projects/trecvid/