Abstract
Due to the rapid growth of digital gadgets with various screen sizes, resolutions and hardware processing capabilities, robust video retargeting is of increasing relevance. An efficient retargeting algorithm should not only retain semantic content, but also maintain spatiotemporal resolution of video data. In this paper, the effective seam carving technique for content-aware video retargeting is discussed. Retargeting video is of immense importance as it is frequently played on several gadgets such as television, mobile, tablet, and notebook. The proposed method considers each video frame as an independent image entity and tries to resize it. Our main contribution is a formulation of seam carving using graph cut method. Convention cut techniques fail to defend a meaningful seam. Single monotonic well connected by pixel to pixel is most desirable property in seam carving process. The traditional seam carving method is designed to work based on the minimum energy concept, while ignoring the energy that has been introduced by the operator. To address this issue, we propose a new design criterion in which least amount of energy is introduced in retargeted video.
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Desai, S.D., Bhille, M., Hiremath, N.D. (2017). Content-Aware Video Retargeting by Seam Carving. In: Satapathy, S., Bhateja, V., Udgata, S., Pattnaik, P. (eds) Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications . Advances in Intelligent Systems and Computing, vol 515. Springer, Singapore. https://doi.org/10.1007/978-981-10-3153-3_15
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DOI: https://doi.org/10.1007/978-981-10-3153-3_15
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