Abstract
The detection of Near-Duplicate Video has been studied by many scholars in recent years. This paper proposes a method for classifying and identifying infringing video by extracting video visual features, obtaining inter-frame relationship graphs, and using CNN classification network. We apply the improved weighting technique of text mining to video solution and still achieve better results. This method is robust in experiments and does not require retraining of a model in practical applications. At the same time, this method can also be applied to large-scale video retrieval. Our method has an F1 score of 95.74%.
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Acknowledgments
This work was mainly supported by the development of digital copyright protection technology scheme based on digital image tamper identification technology, Key Project of Beijing, China (No. Z181100000618006), and also supported by data-driven security production supervision image construction technology and security management situation research (No. Z181100009018003).
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Ai, X., He, Y., Hu, Y., Tian, W. (2019). Inter-frame Relationship Graph Based Near-Duplicate Video Clip Detection Method. In: Wang, Y., Huang, Q., Peng, Y. (eds) Image and Graphics Technologies and Applications. IGTA 2019. Communications in Computer and Information Science, vol 1043. Springer, Singapore. https://doi.org/10.1007/978-981-13-9917-6_8
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DOI: https://doi.org/10.1007/978-981-13-9917-6_8
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