计算机工程与应用2017，Vol.53Issue(21)：190-194,5.DOI:10.3778/j.issn.1002-8331.1606-0319
融合HOG和颜色特征的人体姿态估计新算法
New human pose estimation algorithm based on HOG and color features
摘要
Abstract
The existing human pose estimation algorithm always get the lower accuracy for those images with very poor light conditions and low color contrast. For solving the problem, a more suitable part appearance model based on the Possibilistic C-Means(PCM)clustering algorithm is built by using Histogram of Oriented Gradient(HOG)and color features, and a new human pose estimation algorithm based on the fusion of HOG and color features is proposed. The part appearance model is selected automatically according to the image to be processed, the existing part appearance model based on the fusion of HOG and color features is selected if both the light conditions and color contrast are good, and otherwise the part appearance model based on PCM clustering algorithm is chosen. Simulation results show that the established part appearance model can represent the appearance of real human part, which is from images with very poor light conditions and low color contrast, more accurately, the proposed human posture estimation algorithm can get more accurate estimation results for various types of images to be processed.关键词
人体姿态估计/部位外观模型/梯度方向直方图/颜色/可能性C聚类算法Key words
human pose estimation/part appearance model/histogram of oriented gradient/color/possibilistic C-means clustering algorithm分类
信息技术与安全科学引用本文复制引用
沈建冬,陈恒..融合HOG和颜色特征的人体姿态估计新算法[J].计算机工程与应用,2017,53(21):190-194,5.基金项目
陕西省教育厅自然科学资助项目(No.2013jk1068). （No.2013jk1068）
