An Enhanced em algorithm using maximum entropy distribution as initial condition

Guorong Xuan, Yun-Qing Shi, Peiqi Chai, Patchara Sutthiwan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

The conventional EM algorithms may suffer from the following two problems. First, it may converge to a local maximum. Second, the algorithm may suffer from singularity. A novel Enhanced EM algorithm (EEM) using a realization of maximum-entropy uniform distribution as initial condition is proposed. A global optimal solution can be obtained. In addition, a positive perturbation scheme is adopted to avoid singularity. Experimental results have demonstrated that the EEM is simple and effective compared with some prior arts.

Original languageEnglish (US)
Title of host publicationICPR 2012 - 21st International Conference on Pattern Recognition
Pages849-852
Number of pages4
StatePublished - Dec 1 2012
Event21st International Conference on Pattern Recognition, ICPR 2012 - Tsukuba, Japan
Duration: Nov 11 2012Nov 15 2012

Other

Other21st International Conference on Pattern Recognition, ICPR 2012
Country/TerritoryJapan
CityTsukuba
Period11/11/1211/15/12

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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