{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T04:44:11Z","timestamp":1774586651433,"version":"3.50.1"},"reference-count":38,"publisher":"Tech Science Press","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2025]]},"DOI":"10.32604\/cmc.2024.055732","type":"journal-article","created":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T06:57:27Z","timestamp":1731653847000},"page":"1255-1276","source":"Crossref","is-referenced-by-count":2,"title":["Occluded Gait Emotion Recognition Based on Multi-Scale Suppression Graph Convolutional Network"],"prefix":"10.32604","volume":"82","author":[{"given":"Yuxiang","family":"Zou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiwu","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xunrui","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenhua","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ning","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"17807","published-online":{"date-parts":[[2025]]},"reference":[{"key":"ref1","series-title":"IEEE\/CVF Conf. Comput. Vis. Pattern Recognit.","first-page":"14234","article-title":"Emoticon: Context-aware multimodal emotion recognition using Frege\u2019s principle","author":"Mittal","year":"2020"},{"key":"ref2","series-title":"IEEE\/CVF Int. Conf. Comput. Vis.","first-page":"1140","article-title":"Attention-aware polarity sensitive embedding for affective image retrieval","author":"Yao","year":"2019"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1007\/BF00999605","article-title":"The identification of emotions from gait information","volume":"11","author":"Montepare","year":"Mar. 1987","journal-title":"J. Nonverbal Behav."},{"key":"ref4","doi-asserted-by":"crossref","first-page":"478","DOI":"10.1016\/j.humov.2017.11.008","article-title":"Not all is noticed: Kinematic cues of emotion-specific gait","volume":"57","author":"Halovic","year":"2018","journal-title":"Hum. Mov. Sci."},{"key":"ref5","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1167\/9.6.15","article-title":"Critical features for the perception of emotion from gait","volume":"9","author":"Roether","year":"2009","journal-title":"J. Vis."},{"key":"ref6","series-title":"Proc. IEEE\/CVF Conf. Comput. Vis. Pattern Recognit.","first-page":"13309","article-title":"Gait recognition via semi-supervised disentangled representation learning to identity and covariate features","author":"Li","year":"2020"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1109\/TAFFC.2018.2874986","article-title":"Survey on emotional body gesture recognition","volume":"12","author":"Noroozi","year":"2018","journal-title":"IEEE Trans. Affect. Comput."},{"key":"ref8","series-title":"Proc. AAAI Conf. Artif. Intell.","first-page":"303","article-title":"An end-to-end visual-audio attention network for emotion recognition in user-generated videos","author":"Zhao","year":"2020"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1109\/TPAMI.2020.2998790","article-title":"On learning disentangled representations for gait recognition","volume":"44","author":"Zhang","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref10","first-page":"3467","article-title":"GaitSet: Cross-view gait recognition through utilizing gait as a deep set","volume":"44","author":"Chao","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref11","doi-asserted-by":"crossref","first-page":"1050","DOI":"10.1109\/TSMCB.2010.2044040","article-title":"Recognition of affect based on gait patterns","volume":"40","author":"Karg","year":"2010","journal-title":"IEEE Trans. Syst. Man Cybern. Part B (Cybern.)"},{"key":"ref12","first-page":"1","article-title":"Adaptive real-time emotion recognition from body movements","volume":"5","author":"Wang","year":"2015","journal-title":"ACM Trans. Interact. Intell. Syst."},{"key":"ref13","series-title":"IEEE Int. Conf. Acoust., Speech Signal Process. (ICASSP)","first-page":"3229","article-title":"TNTC: Two-stream network with transformer-based complementarity for gait-based emotion recognition","author":"Hu","year":"2022"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"2592","DOI":"10.1109\/JBHI.2022.3233597","article-title":"EPIC: Emotion perception by spatio-temporal interaction context of gait","volume":"28","author":"Lu","year":"2024","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref15","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1109\/TCSS.2022.3223251","article-title":"Emotion recognition from gait analyses: Current research and future directions","volume":"11","author":"Xu","year":"2024","journal-title":"IEEE Trans. Comput. Soc. Syst."},{"key":"ref16","series-title":"Eur. Conf. Comput. Vis. (ECCV)","first-page":"145","article-title":"Take an emotion walk: Perceiving emotions from gaits using hierarchical attention pooling and affective mapping","author":"Bhattacharya","year":"2020"},{"key":"ref17","unstructured":"T. Randhavane, U. Bhattacharya, K. Kapsaskis, K. Gray, A. Bera and D. Manocha, \u201cIdentifying emotions from walking using affective and deep features,\u201d 2019, arXiv:1906.11884."},{"key":"ref18","article-title":"Hierarchical-attention-based neural network for gait emotion recognition","volume":"37","author":"Zhang","year":"2024, Art. no. 129600","journal-title":"Physica A: Stat. Mech. Appl."},{"key":"ref19","series-title":"2020 IEEE\/RSJ Int. Conf. Intell. Robots Syst. (IROS)","first-page":"8200","article-title":"ProxEmo: Gait-based emotion learning and multi-view proxemic fusion for socially-aware robot navigation","author":"Narayanan","year":"2020"},{"key":"ref20","first-page":"1342","article-title":"Step: Spatial temporal graph convolutional networks for emotion perception from gaits","volume":"34","author":"Bhattacharya","year":"2020","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"ref21","doi-asserted-by":"crossref","first-page":"1634","DOI":"10.1109\/TAFFC.2024.3365694","article-title":"Looking into gait for perceiving emotions via bilateral posture and movement graph convolutional networks","volume":"15","author":"Zhai","year":"2024","journal-title":"IEEE Trans. Affect. Comput."},{"key":"ref22","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2023.110117","article-title":"MSA-GCN: Multiscale adaptive graph convolution network for gait emotion recognition","volume":"147","author":"Yin","year":"2024, Art. no. 110117","journal-title":"Pattern Recognit."},{"key":"ref23","doi-asserted-by":"crossref","first-page":"10288","DOI":"10.1109\/TII.2022.3229140","article-title":"Occlusion-aware graph neural networks for skeleton action recognition","volume":"19","author":"Shi","year":"Oct. 2023","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref24","doi-asserted-by":"crossref","first-page":"1489","DOI":"10.1109\/TMM.2023.3235300","article-title":"Delving deep into one-shot skeleton-based action recognition with diverse occlusions","volume":"25","author":"Peng","year":"2023","journal-title":"IEEE Trans. Multimed."},{"key":"ref25","doi-asserted-by":"crossref","first-page":"2963","DOI":"10.1109\/TIP.2021.3056895","article-title":"Structural knowledge distillation for efficient skeleton-based action recognition","volume":"30","author":"Bian","year":"2021","journal-title":"IEEE Trans. Image Process."},{"key":"ref26","doi-asserted-by":"crossref","first-page":"103352","DOI":"10.1016\/j.jobe.2021.103352","article-title":"Action recognition of construction workers under occlusion","volume":"45","author":"Li","year":"2022","journal-title":"J. Build. Eng."},{"key":"ref27","series-title":"Proc. 2020 9th Int. Conf. Comput. Pattern Recognit.","first-page":"43","article-title":"Generalized graph convolutional networks for action recognition with occluded skeletons","author":"Ding","year":"2020"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1142\/S0129065723500478","article-title":"A deep regression approach for human activity recognition under partial occlusion","volume":"33","author":"Vernikos","year":"2023","journal-title":"Int. J. Neural Syst."},{"key":"ref29","first-page":"1","article-title":"Anti-occlusion infrared aerial target recognition with multisemantic graph skeleton model","volume":"60","author":"Yang","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref30","series-title":"Proc. 30th ACM Int. Conf. Multimed.","first-page":"5477","article-title":"OCR-Pose: Occlusion-aware contrastive representation for unsupervised 3D human pose estimation","author":"Wang","year":"2022"},{"key":"ref31","doi-asserted-by":"crossref","first-page":"4592","DOI":"10.1007\/s10489-022-03589-y","article-title":"An improved spatial temporal graph convolutional network for robust skeleton-based action recognition","volume":"53","author":"Xing","year":"2023","journal-title":"Appl. Intell."},{"key":"ref32","unstructured":"T. N. Kipf and M. Welling, \u201cSemi-supervised classification with graph convolutional networks,\u201d 2016, arXiv:1609.02907."},{"key":"ref33","doi-asserted-by":"crossref","first-page":"1915","DOI":"10.1109\/TCSVT.2020.3015051","article-title":"Richly activated graph convolutional network for robust skeleton-based action recognition","volume":"31","author":"Song","year":"2020","journal-title":"IEEE Trans. Circ. Syst. Video Technol."},{"key":"ref34","series-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR)","first-page":"2921","article-title":"Learning deep features for discriminative localization","author":"Zhou","year":"2016"},{"key":"ref35","doi-asserted-by":"crossref","first-page":"134","DOI":"10.3758\/BF03192758","article-title":"A motion capture library for the study of identity, gender, and emotion perception from biological motion","volume":"38","author":"Ma","year":"2006","journal-title":"Behav. Res. Methods"},{"key":"ref36","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1002\/cav.1762","article-title":"Motion recognition of self and others on realistic 3D avatars","volume":"28","author":"Narang","year":"2017","journal-title":"Comput. Animat. Virtual Worlds"},{"key":"ref37","series-title":"Proc. British Mach. Vis. Conf. (BMVC)","first-page":"119.1\u2013119.12","article-title":"A recurrent variational autoencoder for human motion synthesis","author":"Habibie","year":"2017"},{"key":"ref38","first-page":"7444","article-title":"Spatial temporal graph convolutional networks for skeleton-based action recognition","volume":"32","author":"Yan","year":"2018","journal-title":"Proc. AAAI Conf. Artif. Intell."}],"container-title":["Computers, Materials &amp; Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/file.techscience.com\/files\/cmc\/2025\/TSP_CMC-82-1\/TSP_CMC_55732\/TSP_CMC_55732.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,7]],"date-time":"2025-03-07T06:57:26Z","timestamp":1741330646000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v82n1\/59209"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":38,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2024.055732","relation":{},"ISSN":["1546-2226"],"issn-type":[{"value":"1546-2226","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}