FAST GAUSSIAN MIXTURE CLUSTERING FOR SKIN DETECTION

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

2 Scopus Citations
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Detail(s)

Original languageEnglish
Title of host publication2007 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP 2007 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers, Inc.
PagesIV341-IV344
Volume4
ISBN (print)1424414377, 9781424414376, 9781424414369
Publication statusPublished - Sept 2007

Publication series

Name
ISSN (Print)1522-4880

Conference

Title14th IEEE International Conference on Image Processing (ICIP 2007)
PlaceUnited States
CitySan Antonio
Period16 - 19 September 2007

Abstract

Support vector machine (SVM) is a hot topic in many areas, such as machine learning, computer vision, data mining, and so on, due to its powerful ability to perform classification. Though there exist a lot of approaches to improve the accuracy and the efficiency of the models of SVM, few of them address how to eliminate the redundant data from the input training vectors. As it is known, most of support vectors distributes in the boundary of the class, which means the vectors in the center of the class are useless. In the paper, we propose a new approach based on Gaussian model to preserve the training vectors in the boundary of the class and eliminate the training vectors in the center of the class. The experiments show that our approach can reduce most of the input training vectors and preserve the support vectors at the same time, which leads to a significant reduction in the computational cost and maintains the accuracy.

Research Area(s)

  • Image segmentation, Support vector machine

Citation Format(s)

FAST GAUSSIAN MIXTURE CLUSTERING FOR SKIN DETECTION. / Yu, Zhiwen; Wong, Hau-San.
2007 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP 2007 - Proceedings. Vol. 4 Institute of Electrical and Electronics Engineers, Inc., 2007. p. IV341-IV344 4380024.

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review