Abstract
The K-means clustering algorithm has been widely adopted to build vocabulary in image retrieval. But, the speed and accuracy of K-means still need to be improved. In the manuscript, we propose a New Parallel Hierarchical K-means Clustering (PHKM) Algorithm for Video Retrieval. The PHKM algorithm improves on the K-means as the following ways. First, the Hellinger kernel is used to replace the Euclidean kernel, which improves the accuracy. Second, the multi-core processors based parallel clustering algorithm is proposed. The experiment results show that the proposed PHKM algorithm is very faster and effective than K-means.
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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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Liao, K., Tang, Z., Cao, C., Zhao, F., Zheng, Y. (2017). A New Parallel Hierarchical K-Means Clustering Algorithm for Video Retrieval. 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_23
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DOI: https://doi.org/10.1007/978-981-10-3530-2_23
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