An improved SalBayes model with GMM

Authors:
Hairu Guo;Xiaojie Wang;Yixin Zhong;Song Bi
Affiliations:
Center for Intelligence Science and Technology, Beijing University of Posts and Telecommunications, Beijing, China and College of Computer Science and Technology, Henan Polytechnic University, Jia ...;Center for Intelligence Science and Technology, Beijing University of Posts and Telecommunications, Beijing, China;Center for Intelligence Science and Technology, Beijing University of Posts and Telecommunications, Beijing, China;Center for Intelligence Science and Technology, Beijing University of Posts and Telecommunications, Beijing, China
Venue:
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
Year:
2011

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Abstract

SalBayes is an efficient visual attention model. We describe an improved SalBayes model with Gaussian Mixture Model (GMM) which can fit the object with various transformations better. The improved model learns the probability of an object's visual appearance within a particular feature map, and the Probability Distribution Function (PDF) is modeled using a Mixture Gaussian distribution for each individual feature. The results tested on Amsterdam Library of Object Images (ALOI) shows the better performance than that with the original model.