电子科技大学学报2024，Vol.53Issue(6)：930-939,10.DOI:10.12178/1001-0548.2023233
复杂运动场景下的多人姿态估计研究
Research on Multiplayer Pose Estimation in Complex Sports Scenes
摘要
Abstract
In terms of the problems such as mutual occlusion,self-occlusion,sports equipment occlusion and complex background interference among athletes in motion scenes,a high-resolution feature generation recovery network is proposed in this paper.The attention fusion mechanism is introduced to screen the useful feature information channels.The deconvolution and multi-scale feature fusion modules are added to deal with the pose estimation tasks for small target portraits and large and medium-sized target portraits in a hierarchical manner.The adversarial module is designed and generated to complete and predict the missing parts to obtain the keypoint heat map,the keypoint connection mode is determined through the pose skeleton and the optimal matching algorithm,and the visual pose estimation results are output.Experimental results on MSCOCO and Crowd Pose datasets have showed that the pose estimation method is more effective in complex motion scenes.关键词
人体姿态估计/深度学习/复杂运动场景/融合注意力机制/生成对抗网络Key words
human pose estimation/deep learning/complex motion scenes/fusion attention mechanisms/generate adversarial networks分类
信息技术与安全科学引用本文复制引用
柳长源,臧彦丞,兰朝凤..复杂运动场景下的多人姿态估计研究[J].电子科技大学学报,2024,53(6):930-939,10.基金项目
国家自然科学基金(11804068) （11804068）
黑龙江省交通运输厅科技项目(HJK2024B002) （HJK2024B002）
