Abstract: Human pose estimation is a research topic which has wide application prospect, and the topic has become one of the important research hotspot in the field of computer vision. For feature extraction in human pose estimation, the paper proposes an improved method based on Binary Phase-Only Filter（BPOF） algorithm, first of all, it calculates the scanning line length value from eight directions of every pixel in the image, then puts the eight value into the BPOF algorithm to get the feature of the pixel, it also optimizes the random forest which is used to classify, finally can estimate the human pose. The improved method has made a very big enhancement in recognition rate and robustness, at the same time, the optimized random forest classifier reduces the algorithm system time consumption.

Key words: computer vision, human pose, depth image, Binary Phase-Only Filter（BPOF）, random forest

摘要： 人体姿态估计是一个有着非常广泛应用前景的研究课题，并且在计算机视觉领域中，该课题已经成为了重要研究热点之一。针对人体姿态估计中的特征表达提出了一种基于二元纯位相匹配滤波器（BPOF）的特征提取算法，首先对图像中每一个像素点都从8个方向去计算扫描线段长度值，然后再将得到的8个值引入到BPOF算法中进行计算以便得到该像素点的特征值，同时针对随机森林分类器进行优化，最终对图像中的人体姿态做出估计。该改进方法在识别率以及鲁棒性方面有了很大提高，同时优化的随机森林分类器使得算法系统时间开销有所降低。

关键词: 计算机视觉, 人体姿态, 深度图像, 二元纯位相匹配滤波器（BPOF）, 随机森林