ICIP 2006, Atlanta, GA
 

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Atlanta Conv. & Vis. Bureau

 

Technical Program

Paper Detail

Paper:WP-P1.2
Session:Visual Object/Event Detection, Segmentation, and Classification
Time:Wednesday, October 11, 14:20 - 17:00
Presentation: Poster
Title: FAST GAUSSIAN MIXTURE CLUSTERING FOR SKIN DETECTION
Authors: Zhiwen Yu; City University of Hong Kong 
 Hau-San Wong; City University of Hong Kong 
Abstract: EM is one of the popular algorithms which can be applied to skin segmentation. Due to the high computational cost of EM, traditional EM is difficult to apply to a large skin database. Inspired by the idea of subsampling, we integrate EM with incremental clustering and hierarchical clustering to estimate the parameters of mixture models. The algorithm first selects the samples by the incremental clustering approach and hierarchical clustering approach. Then, EM is applied to the sample set. The experiments show that the new EM algorithm works well in the skin database.