Abstract
In this paper, an unequally weighted video hashing algorithm is presented, in which visual saliency is used to generate the video hash and weight different hash bits. The proposed video hash is fused by two hashes, which are the spatio-temporal hash (ST-Hash) generated according to the spatio-temporal video information and the visual hash (V-Hash) generated according to the visual saliency distribution. In order to emphasize the contribution of visual salient regions to video content, Weighted Error Rate (WER) is defined as an unequally weighted hash matching method to take the place of BER. The WER, unlike BER, gives hash bits unequal weights according to their corresponding visual saliency in hash matching. Experiments verify the robustness and discrimination of the proposed video hashing algorithm and show that the WER-based hash matching is helpful to achieve better precision rate and recall rate.
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Sun, J., Wang, J., Yuan, H., Liu, X., Liu, J. (2013). Unequally Weighted Video Hashing for Copy Detection. In: Li, S., et al. Advances in Multimedia Modeling. MMM 2013. Lecture Notes in Computer Science, vol 7732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35725-1_50
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DOI: https://doi.org/10.1007/978-3-642-35725-1_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35724-4
Online ISBN: 978-3-642-35725-1
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