{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:28:44Z","timestamp":1760149724200,"version":"build-2065373602"},"reference-count":45,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2023,9,3]],"date-time":"2023-09-03T00:00:00Z","timestamp":1693699200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fundamental Research Funds for the Central Universities","award":["2022WKYXZX019","22YJC890005","HBSK2022YB562","2023AFB359","G1323522067"],"award-info":[{"award-number":["2022WKYXZX019","22YJC890005","HBSK2022YB562","2023AFB359","G1323522067"]}]},{"name":"Humanity and Social Science Youth Foundation of Ministry of Education of China","award":["2022WKYXZX019","22YJC890005","HBSK2022YB562","2023AFB359","G1323522067"],"award-info":[{"award-number":["2022WKYXZX019","22YJC890005","HBSK2022YB562","2023AFB359","G1323522067"]}]},{"name":"Hubei Province Social Science Fund General Project (subsequent funding)","award":["2022WKYXZX019","22YJC890005","HBSK2022YB562","2023AFB359","G1323522067"],"award-info":[{"award-number":["2022WKYXZX019","22YJC890005","HBSK2022YB562","2023AFB359","G1323522067"]}]},{"name":"Hubei Natural Science Foundation Youth Project","award":["2022WKYXZX019","22YJC890005","HBSK2022YB562","2023AFB359","G1323522067"],"award-info":[{"award-number":["2022WKYXZX019","22YJC890005","HBSK2022YB562","2023AFB359","G1323522067"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["2022WKYXZX019","22YJC890005","HBSK2022YB562","2023AFB359","G1323522067"],"award-info":[{"award-number":["2022WKYXZX019","22YJC890005","HBSK2022YB562","2023AFB359","G1323522067"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Human pose estimation is the basis of many downstream tasks, such as motor intervention, behavior understanding, and human\u2013computer interaction. The existing human pose estimation methods rely too much on the similarity of keypoints at the image feature level, which is vulnerable to three problems: object occlusion, keypoints ghost, and neighbor pose interference. We propose a dual-space-driven topology model for the human pose estimation task. Firstly, the model extracts relatively accurate keypoints features through a Transformer-based feature extraction method. Then, the correlation of keypoints in the physical space is introduced to alleviate the error localization problem caused by excessive dependence on the feature-level representation of the model. Finally, through the graph convolutional neural network, the spatial correlation of keypoints and the feature correlation are effectively fused to obtain more accurate human pose estimation results. The experimental results on real datasets also further verify the effectiveness of our proposed model.<\/jats:p>","DOI":"10.3390\/s23177626","type":"journal-article","created":{"date-parts":[[2023,9,4]],"date-time":"2023-09-04T02:59:55Z","timestamp":1693796395000},"page":"7626","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["DSPose: Dual-Space-Driven Keypoint Topology Modeling for Human Pose Estimation"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-0867-3397","authenticated-orcid":false,"given":"Anran","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-9065-6493","authenticated-orcid":false,"given":"Jingli","family":"Li","sequence":"additional","affiliation":[{"name":"School of Physical Education, Huazhong University of Science and Technology, Wuhan 430074, China"},{"name":"Sport and Health Initiative, Optical Valley Laboratory, Wuhan 430074, China"}]},{"given":"Hongtao","family":"Zeng","sequence":"additional","affiliation":[{"name":"School of Physical Education, Huazhong University of Science and Technology, Wuhan 430074, China"},{"name":"Sport and Health Initiative, Optical Valley Laboratory, Wuhan 430074, China"}]},{"given":"Hongren","family":"Cheng","sequence":"additional","affiliation":[{"name":"Sports Big-Data Research Center, Wuhan Sports University, Wuhan 430079, China"}]},{"given":"Liangshan","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Physical Education, China University of Geosciences, Wuhan 430074, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Shotton, J., Fitzgibbon, A., Cook, M., Sharp, T., Finocchio, M., Moore, R., Kipman, A., and Blake, A. 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