关键词: 人体姿态估计, 部位外观模型, 支持向量数据描述, 梯度方向直方图, 权重系数

Abstract: The Support Vector Data Description（SVDD） algorithm is one of the best way to solve the problem of single class classification, it has been applied sucessfully in the human pose estimation problem, and good results have been achieved in the establishment of the part appearance model. However, all of the training samples and different feature of sample in the existing part appearance models, which are built by the SVDD algorithm, are treated equally. For overcoming these two defects, a sample and feature weighted SVDD algorithm is proposed, and a part appearance model based on sample and feature weighted SVDD algorithm is constructed. The weighting coefficient of sample is determined by the distance between the sample and sample center, the weighting coefficient of feature is computed according to the number that the corresponding image regions in the training images of sample feature are contained by the real human part. The experiment results show that the proposed part appearance model can represent the appearance of real human part more accurately than the part appearance model based on the standard SVDD algorithm, and the higher accuracy of human pose estimation can be got.

Key words: human pose estimation, part appearance model, Support Vector Data Description（SVDD）, histogram of oriented gradient, weighting coefficient