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联合关键点数据增强和结构先验的遮挡人体姿态估计

韩刚涛 王昊 汪松 陈恩庆

计算机工程与应用2024,Vol.60Issue(20):254-261,8.
计算机工程与应用2024,Vol.60Issue(20):254-261,8.DOI:10.3778/j.issn.1002-8331.2307-0139

联合关键点数据增强和结构先验的遮挡人体姿态估计

Joint Keypoint Data Augmentation and Structural Prior for Occluded Human Pose Estimation

韩刚涛 1王昊 1汪松 1陈恩庆1

作者信息

  • 1. 郑州大学 电气与信息工程学院,郑州 450001
  • 折叠

摘要

Abstract

Human pose estimation techniques have important applications in many fields.Existing studies focus on the precise localization of human keypoints without occlusion,but ignore the prevalent occlusion problem in the process of human image acquisition.To address this problem,a human pose estimation method based on keypoint data augmentation is proposed.Specifically,the data augmentation strategy generates a specific number and size of occlusion regions cen-tered on the human visible keypoints in the training images to simulate the scenes when the human keypoints are occluded and to improve the robustness of the network model for keypoint prediction under the occlusion scenes.In order to improve the model's perception of the correlation between the occluded keypoints and the adjacent keypoints,a loss function based on the priori knowledge of the human body structure is further designed to construct the adjacent keypoint connec-tions based on the real structure of the human body and constrain the predicted keypoint coordinate range,so as to improve the coordinate accuracy of the occluded keypoints.The prediction results on the OCHuman test set and COCO validation set show that the method can improve the performance of human pose estimation in occluded scenes without increasing the network parameters compared with the benchmark network model.

关键词

人体姿态估计/关键点级遮挡/数据增强/人体结构损失

Key words

human pose estimation/keypoint-level occlusion/data augmentation/human structure loss

分类

信息技术与安全科学

引用本文复制引用

韩刚涛,王昊,汪松,陈恩庆..联合关键点数据增强和结构先验的遮挡人体姿态估计[J].计算机工程与应用,2024,60(20):254-261,8.

基金项目

国家自然科学基金(62301497,62101504) (62301497,62101504)

河南省科技攻关项目(222102210102) (222102210102)

嵩山实验室项目(221100211300-01) (221100211300-01)

嵩山实验室预研项目(YYJC022022002). (YYJC022022002)

计算机工程与应用

OA北大核心CSTPCD

1002-8331

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