Extreme Learning Machine Based Hand Posture Recognition in Color-Depth Image

摘要：

　　Hand posture recognition is one of the most challenging problems in the computer vision field,especially in the scenes with complex background and illumination variance.This paper presents a real time hand posture recognition method in color-depth image.To accurately locate hands in the images with complex background,a depth histogram based adaptive thresholding method is adopted for the depth image and a Bayesian skin-color detection is performed for the corresponding color image.Then two processed results are fused and refined with a region-growing method.Finally,the histogram of gradients feature of the hand posture is computed for Extreme Learning Machine classifier to recognize different postures.Experiments show that the proposed hand posture recognition method runs in real-time and achieves high recognition accuracy.

关键词： Hand detection posture recognition Extreme Learning Machine HOG feature extraction

作者: Zhen Zhou Shutao Li Bin Sun

作者单位: College of Electrical and Information Engineering,Hunan University,Changsha,China,410082

会议类型: 国际会议

会议名称: Chinese Conference on Pattern Recognition, CCPR(2014年全国模式识别学术会议)

会议地点: 长沙

会议语种:英文

页码: 276-285

在线出版日期: 2014-11-01（万方平台首次上网日期，不代表论文的发表时间）