Abstract
Shot boundary detection is the first and the most crucial step towards video content management applications including indexing, retrieval and summerisation. In this paper, an abrupt transition detection algorithm has been proposed based on phase congruency feature of the frames. The phase congruency feature is insensitive to illumination variation, change in contrast and scale. Besides this, it captures edges, corners and structural information of the frames. Motivated by this, a PC-based similarity measure is proposed for illumination insensitive video cut detection. The proposed approach is experimentally validated with standard algorithms available in the literature using TRECVid data set and other publicly available videos. The favourable results are in agreement with the proposed model.
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Kar, T., Kanungo, P., Jha, V. (2022). Illumination Insensitive Video Cut Detection Using Phase Congruency. In: Mandal, J.K., Hsiung, PA., Sankar Dhar, R. (eds) Topical Drifts in Intelligent Computing. ICCTA 2021. Lecture Notes in Networks and Systems, vol 426. Springer, Singapore. https://doi.org/10.1007/978-981-19-0745-6_34
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DOI: https://doi.org/10.1007/978-981-19-0745-6_34
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