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 the 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 features’ 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.
This work was supported by the Korea research Foundation Grant (KRF-2006-005-J03801).
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Ko, KC., Cheon, YM., Kim, GY., Choi, H. (2007). Robust Scene Change Detection Algorithm for Flashlights. In: Gervasi, O., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2007. ICCSA 2007. Lecture Notes in Computer Science, vol 4705. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74472-6_82
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DOI: https://doi.org/10.1007/978-3-540-74472-6_82
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