A fast randomized clustering method based on a hypothetical potential field

Yonggang Lu; Li Liao; Ruhai Wang

doi:10.1117/12.902696

2 December 2011 A fast randomized clustering method based on a hypothetical potential field

Yonggang Lu, Li Liao, Ruhai Wang

Proceedings Volume 8004, MIPPR 2011: Pattern Recognition and Computer Vision; 800403 (2011) https://doi.org/10.1117/12.902696
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

A novel randomized clustering method is proposed to overcome some of the drawbacks of Mean Shift method. A hypothetical potential field is constructed from all the data points. Different from Mean Shift which moves the kernel window towards high-density region, our method moves the kernel window towards low-potential region. The proposed method is evaluated by comparing with both Mean Shift and K-means++ on three synthetic data sets which represent the clusters of different sizes, different shapes and different distributions. The experiments show that our method can produce more accurate results than both Mean Shift and K-means++.

Citation Download Citation

Yonggang Lu, Li Liao, and Ruhai Wang "A fast randomized clustering method based on a hypothetical potential field", Proc. SPIE 8004, MIPPR 2011: Pattern Recognition and Computer Vision, 800403 (2 December 2011); https://doi.org/10.1117/12.902696

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