FEATURE SELECTION COMBINED EYE TRACKING DATA AND IMAGE CLASSIFICATION

摘要：

Image classification often relies heavily on effective image descriptors.In this paper, a feature selection algorithm based on eye tracking data is proposed.This algorithm integrates the classification result based on support vector machines (SVMs) and mutual information difference (MID).In this method, regions of interest obtained based on the eye tracking data are used to represent the image.Then almost all low-level features collected are extracted for describing the above image regions.The SVMs classifier is used to perform a rough selection, while MID is used to obtain a smaller subset.Experimental results show significant improvement for feature selection by incorporating eye tracking data.

关键词： Eye tracking data Feature selection SVMs MID Regions of interest

作者: HUI YU JIAJUN WANG

作者单位: School of Electronic and Information Engineering,Soochow University

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer Technology and Development(2011第三届计算机技术与发展国际会议 ICCTD2011)

会议地点: 成都

会议语种:英文

页码: 2185-2189

在线出版日期: 2011-11-25（万方平台首次上网日期，不代表论文的发表时间）