Robust scene change detection algorithm for flashlights

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Abstract

Flashlights in video cause abrupt brightness changes of a scene and will be detected as false scene change if not handled properly. So in this paper propose a robust scene change detection algorithm which can detect the scene change correctly by skipping for the flashing period. At first, the proposed methods make use of histogram comparison which are simple and more robust to object and camera movement while enough spatial information is retained to produce more accurate difference values from consecutive frames. The normalized works of difference values are performed to solve tile optimal threshold decision problem. Normalized difference values are dynamically compressed by Log metrics and more efficient to detect scene boundary. Finally, we distinguish flashlights from difference values by applying a 'flashlights reatares' which are defined based on the temporal property of normalized difference values across a frame sequence. The proposed methods are tested on the various video types and experimental results show that the proposed algorithms are effective and reliably detect scene changes. © Springer-Verlag Berlin Heidelberg 2007.

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APA

Ko, K. C., Cheon, Y. M., Kim, G. Y., & Choi, H. I. (2007). Robust scene change detection algorithm for flashlights. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4705 LNCS, pp. 1003–1013). Springer Verlag. https://doi.org/10.1007/978-3-540-74472-6_82

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