Abstract
The amount of video surveillance cameras and with that the amount of recorded data is enormous. Thus, efficient methods for using and analyzing this data have to be found. In this paper, we propose VideoZoom, an interactive system for summarization, browsing and retrieval of video data which is specifically designed to support a human operator in the video analysis task in the visual surveillance domain. The main contributions of this paper are: i) a visualization technique for efficient browsing, using an interactive zooming interface to present video summaries on layers of increasing information detail, and ii) a video retrieval component which allows for interactive retrieval employing a sparse representation of video snippets using local features and bag-of-words like signatures. We hereby present the first integrated system for video browsing with integrated video retrieval technology specifically targeted as assistance system for the visual surveillance domain.
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References
Ajmal, M., Ashraf, M.H., Shakir, M., Abbas, Y., Shah, F.A.: Video summarization: Techniques and classification. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds.) ICCVG 2012. LNCS, vol. 7594, pp. 1–13. Springer, Heidelberg (2012)
Money, A.G., Agius, H.W.: Video summarisation: A conceptual framework and survey of the state of the art. J. Visual Communication and Image Representation 19, 121–143 (2008)
Smeulders, A.W.M., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-based image retrieval at the end of the early years. IEEE Trans. Pattern Anal. Mach. Intell. 22, 1349–1380 (2000)
Schoeffmann, K., Taschwer, M., Böszörmnyi, L.: The video explorer: a tool for navigation and searching within a single video based on fast content analysis. In: Chi Feng, W., Mayer-Patel, K. (eds.) MMSys, pp. 247–258. ACM (2010)
Pritch, Y., Ratovitch, S., Hendel, A., Peleg, S.: Clustered synopsis of surveillance video. In: 2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance, pp. 195–200 (2009)
Yuk, J.S.-C., Wong, K.-Y.K., Chung, R.H.-Y., Chow, K.P., Chin, F.Y.-L., Tsang, K.S.-H.: Object-based surveillance video retrieval system with real-time indexing methodology. In: Kamel, M.S., Campilho, A. (eds.) ICIAR 2007. LNCS, vol. 4633, pp. 626–637. Springer, Heidelberg (2007)
Pritch, Y., Rav-Acha, A., Gutman, A., Peleg, S.: Webcam synopsis: Peeking around the world. In: IEEE ICCV, pp. 1–8 (2007)
Kaewtrakulpong, P., Bowden, R.: An improved adaptive background mixture model for realtime tracking with shadow detection. In: Proceedings of 2nd European Workshop on Advanced Video Based Surveillance Systems, pp. 135–144 (2001)
Blunsden, S., Versino, C.: Content-based image retrieval at the end of the early years. UR - Scientific and Technical Research Reports (2011)
Bay, H., Ess, A., Tuytelaars, T., Gool, L.V.: Surf: Speeded up robust features. Computer Vision and Image Understanding (CVIU) 110, 346–359 (2008)
Oh, S.: et al.: A large-scale benchmark dataset for event recognition in surveillance video. In: IEEE CVPR, pp. 3153–3160 (2011)
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Juengling, K., Blunsden, S., Versino, C. (2014). VideoZoom: An Interactive System for Video Summarization, Browsing and Retrieval. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2014. Lecture Notes in Computer Science, vol 8887. Springer, Cham. https://doi.org/10.1007/978-3-319-14249-4_31
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DOI: https://doi.org/10.1007/978-3-319-14249-4_31
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