Abstract
Local interest points serve as an elementary building block in many video retrieval algorithms, and most of them exploit the local volume features using a Bag of Features (BOF) representation. Such representation, however, ignores potentially valuable information about the global distribution of interest points. In this paper, we first present an R feature to capture the detailed global geometrical distribution of interest points. Then, we propose a fusion strategy to combine the BOF representation with the global R feature for further improving recognition accuracy. Convincing experimental results on several publicly available datasets demonstrate that the proposed approach outperforms the state-of-the-art approaches in video retrieval.
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Acknowledgements
This work is supported by the National Natural Science Foundation of China Project No. 61671376, 11272253 and Natural Science Foundation of Shaanxi Province No. 2016JM6022.
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Zhang, M., Liao, K., Cao, C., Zhao, F., Zheng, Y. (2017). BOF Image/Video Retrieval Model with Global Feature. In: Zhao, P., Ouyang, Y., Xu, M., Yang, L., Ouyang, Y. (eds) Advanced Graphic Communications and Media Technologies . PPMT 2016. Lecture Notes in Electrical Engineering, vol 417. Springer, Singapore. https://doi.org/10.1007/978-981-10-3530-2_30
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DOI: https://doi.org/10.1007/978-981-10-3530-2_30
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