Accurate Human Parsing Model by Edge Contour and Pose Feature

Abstract

<p indent=0mm>To address the problem of low accuracy and precision of human parsing due to human pose, edge contour, complexity of clothing accessories and occlusions of human pose joints in dressing scenes, an accurate human parsing model with edge contour and pose features is proposed for dressed human. Firstly, the backbone network based on ResNet-101 is used to represent input human body images and extract the coarse parsing features. Secondly, the edge contour module combining the global and local features after upsampling is constructed to obtain the edge contour of human body. Then, the defined human pose loss function based on human pose is added into pose estimation module to acquire pose features. Finally, coarse parsing feature, edge contour and pose features are integrated into accuracy parsing module, and the accurate human parsing results are output by the combined function of structure loss function and human parsing loss function. The experimental results show that the proposed model can effectively improve 1.96% of mIoU and accuracy on human datasets with more accurate segmentation results for different poses and occlusions of the human body parts.