{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T23:04:47Z","timestamp":1774479887532,"version":"3.50.1"},"reference-count":32,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2025,4,15]],"date-time":"2025-04-15T00:00:00Z","timestamp":1744675200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["62177012"],"award-info":[{"award-number":["62177012"]}]},{"name":"National Natural Science Foundation of China","award":["62267003"],"award-info":[{"award-number":["62267003"]}]},{"name":"National Natural Science Foundation of China","award":["2024GXNSFDA010048"],"award-info":[{"award-number":["2024GXNSFDA010048"]}]},{"name":"National Natural Science Foundation of China","award":["GXKL06240107"],"award-info":[{"award-number":["GXKL06240107"]}]},{"name":"National Natural Science Foundation of China","award":["YCBZ2024160"],"award-info":[{"award-number":["YCBZ2024160"]}]},{"name":"National Natural Science Foundation of China","award":["2023KY1870"],"award-info":[{"award-number":["2023KY1870"]}]},{"name":"Guangxi Natural Science Foundation under Grant","award":["62177012"],"award-info":[{"award-number":["62177012"]}]},{"name":"Guangxi Natural Science Foundation under Grant","award":["62267003"],"award-info":[{"award-number":["62267003"]}]},{"name":"Guangxi Natural Science Foundation under Grant","award":["2024GXNSFDA010048"],"award-info":[{"award-number":["2024GXNSFDA010048"]}]},{"name":"Guangxi Natural Science Foundation under Grant","award":["GXKL06240107"],"award-info":[{"award-number":["GXKL06240107"]}]},{"name":"Guangxi Natural Science Foundation under Grant","award":["YCBZ2024160"],"award-info":[{"award-number":["YCBZ2024160"]}]},{"name":"Guangxi Natural Science Foundation under Grant","award":["2023KY1870"],"award-info":[{"award-number":["2023KY1870"]}]},{"name":"Guangxi Wireless Broadband Communication and Signal Processing Key Laboratory","award":["62177012"],"award-info":[{"award-number":["62177012"]}]},{"name":"Guangxi Wireless Broadband Communication and Signal Processing Key Laboratory","award":["62267003"],"award-info":[{"award-number":["62267003"]}]},{"name":"Guangxi Wireless Broadband Communication and Signal Processing Key Laboratory","award":["2024GXNSFDA010048"],"award-info":[{"award-number":["2024GXNSFDA010048"]}]},{"name":"Guangxi Wireless Broadband Communication and Signal Processing Key Laboratory","award":["GXKL06240107"],"award-info":[{"award-number":["GXKL06240107"]}]},{"name":"Guangxi Wireless Broadband Communication and Signal Processing Key Laboratory","award":["YCBZ2024160"],"award-info":[{"award-number":["YCBZ2024160"]}]},{"name":"Guangxi Wireless Broadband Communication and Signal Processing Key Laboratory","award":["2023KY1870"],"award-info":[{"award-number":["2023KY1870"]}]},{"name":"Innovation Project of Guangxi Graduate Education","award":["62177012"],"award-info":[{"award-number":["62177012"]}]},{"name":"Innovation Project of Guangxi Graduate Education","award":["62267003"],"award-info":[{"award-number":["62267003"]}]},{"name":"Innovation Project of Guangxi Graduate Education","award":["2024GXNSFDA010048"],"award-info":[{"award-number":["2024GXNSFDA010048"]}]},{"name":"Innovation Project of Guangxi Graduate Education","award":["GXKL06240107"],"award-info":[{"award-number":["GXKL06240107"]}]},{"name":"Innovation Project of Guangxi Graduate Education","award":["YCBZ2024160"],"award-info":[{"award-number":["YCBZ2024160"]}]},{"name":"Innovation Project of Guangxi Graduate Education","award":["2023KY1870"],"award-info":[{"award-number":["2023KY1870"]}]},{"name":"Project for Improving the Basic Scientific Research Abilities of Young and Middle-aged Teachers in Guangxi Colleges and Universities","award":["62177012"],"award-info":[{"award-number":["62177012"]}]},{"name":"Project for Improving the Basic Scientific Research Abilities of Young and Middle-aged Teachers in Guangxi Colleges and Universities","award":["62267003"],"award-info":[{"award-number":["62267003"]}]},{"name":"Project for Improving the Basic Scientific Research Abilities of Young and Middle-aged Teachers in Guangxi Colleges and Universities","award":["2024GXNSFDA010048"],"award-info":[{"award-number":["2024GXNSFDA010048"]}]},{"name":"Project for Improving the Basic Scientific Research Abilities of Young and Middle-aged Teachers in Guangxi Colleges and Universities","award":["GXKL06240107"],"award-info":[{"award-number":["GXKL06240107"]}]},{"name":"Project for Improving the Basic Scientific Research Abilities of Young and Middle-aged Teachers in Guangxi Colleges and Universities","award":["YCBZ2024160"],"award-info":[{"award-number":["YCBZ2024160"]}]},{"name":"Project for Improving the Basic Scientific Research Abilities of Young and Middle-aged Teachers in Guangxi Colleges and Universities","award":["2023KY1870"],"award-info":[{"award-number":["2023KY1870"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Estimating human posture in crowded smart teaching environments is a fundamental technical challenge for measuring learners\u2019 engagement levels. This work presents a model for detecting critical points in human posture using ECAv2-HRNet in crowded situations. The paper introduces a method called ECAv2Net, which combines a channel feature reinforcement method with the ECANet attention mechanism network, this innovation improves the performance of the network. Additionally, ECAv2Net is integrated into the high-resolution network HRNet to create ECAv2-HRNet. This fusion allows for the incorporation of more useful feature information without increasing the model parameters. The paper also presents a human posture dataset called GUET CLASS PICTURE, which is designed for dense scenes. The experimental results when using this dataset, as well as a public dataset, demonstrate the superior performance of the human posture estimation model based on ECAv2-HRNet proposed in this paper.<\/jats:p>","DOI":"10.3390\/info16040313","type":"journal-article","created":{"date-parts":[[2025,4,15]],"date-time":"2025-04-15T09:41:11Z","timestamp":1744710071000},"page":"313","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Accurately Estimate and Analyze Human Postures in Classroom Environments"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2429-5782","authenticated-orcid":false,"given":"Zhaoyu","family":"Shou","sequence":"first","affiliation":[{"name":"School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China"},{"name":"Guangxi Wireless Broadband Communication and Signal Processing Key Laboratory, Guilin University of Electronic Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongbo","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongxu","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianwen","family":"Mo","sequence":"additional","affiliation":[{"name":"School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6402-2183","authenticated-orcid":false,"given":"Huibing","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer and Information Security, Guilin University of Electronic Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7907-2853","authenticated-orcid":false,"given":"Jingwei","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer and Information Security, Guilin University of Electronic Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziyong","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Nanning University, Nanning 541699, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7868","DOI":"10.1109\/JSEN.2021.3139588","article-title":"A wearable sensor network with embedded machine learning for real-time motion analysis and complex posture detection","volume":"22","author":"Mascret","year":"2021","journal-title":"IEEE Sens. J."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3603618","article-title":"Deep learning-based human pose estimation: A survey","volume":"56","author":"Zheng","year":"2023","journal-title":"ACM Comput. Surv."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3115","DOI":"10.1007\/s00530-022-01019-0","article-title":"2D Human pose estimation: A survey","volume":"29","author":"Chen","year":"2023","journal-title":"Multimed. Syst."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Zhang, C., Chen, J., Li, J., Peng, Y., and Mao, Z. (2023). Large language models for human\u2013robot interaction: A review. Biomim. Intell. Robot., 3.","DOI":"10.1016\/j.birob.2023.100131"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"125878","DOI":"10.1016\/j.eswa.2024.125878","article-title":"Predicting flow status of a flexible rectifier using cognitive computing","volume":"264","author":"Peng","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"7157","DOI":"10.1109\/TPAMI.2022.3222784","article-title":"Alphapose: Whole-body regional multi-person pose estimation and tracking in real-time","volume":"45","author":"Fang","year":"2022","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_7","unstructured":"Jiang, T., Lu, P., Zhang, L., Ma, N., Han, R., Lyu, C., Li, Y., and Chen, K. (2023). Rtmpose: Real-time multi-person pose estimation based on mmpose. arXiv."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"27709","DOI":"10.1109\/JSEN.2023.3322987","article-title":"Efficient pose estimation via a lightweight single-branch pose distillation network","volume":"23","author":"Zhang","year":"2023","journal-title":"IEEE Sens. J."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Holmquist, K., and Wandt, B. (2023, January 1\u20136). Diffpose: Multi-hypothesis human pose estimation using diffusion models. Proceedings of the IEEE\/CVF International Conference on Computer Vision, Paris, France.","DOI":"10.1109\/ICCV51070.2023.01464"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Tang, Z., Qiu, Z., Hao, Y., Hong, R., and Yao, T. (2023, January 17\u201324). 3D human pose estimation with spatio-temporal criss-cross attention. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, BC, Canada.","DOI":"10.1109\/CVPR52729.2023.00464"},{"key":"ref_11","unstructured":"Tang, Z., Qiu, Z., Hao, Y., Hong, R., and Yao, T. (2023, January 17\u201324). Poseformerv2: Exploring frequency domain for efficient and robust 3d human pose estimation. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, BC, Canada."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3919","DOI":"10.1109\/TSMC.2023.3234611","article-title":"Multi-Person Pose Estimation in the Wild: Using Adversarial Method to Train a Top-Down Pose Estimation Network","volume":"53","author":"Zhang","year":"2023","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1109\/JPROC.2023.3238524","article-title":"Object detection in 20 years: A survey","volume":"111","author":"Zou","year":"2023","journal-title":"Proc. IEEE"},{"key":"ref_14","first-page":"38571","article-title":"Vitpose: Simple vision transformer baselines for human pose estimation","volume":"35","author":"Xu","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3349","DOI":"10.1109\/TPAMI.2020.2983686","article-title":"Deep high-resolution representation learning for visual recognition","volume":"43","author":"Wang","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Bao, W., Niu, T., Wang, N., and Yang, X. (2023). Pose estimation and motion analysis of ski jumpers based on ECA-HRNet. Sci. Rep., 13.","DOI":"10.1038\/s41598-023-32893-x"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Wang, Q., Wu, B., Zhu, P., Li, P., Zuo, W., and Hu, Q. (2020, January 13\u201319). ECA-Net: Efficient channel attention for deep convolutional neural networks. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Seattle, WA, USA.","DOI":"10.1109\/CVPR42600.2020.01155"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Dong, C., and Du, G. (2024). An enhanced real-time human pose estimation method based on modified YOLOv8 framework. Sci. Rep., 14.","DOI":"10.1038\/s41598-024-58146-z"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Li, Q., Zhang, Z., Xiao, F., Zhang, F., and Bhanu, B. (2022). Dite-HRNet: Dynamic lightweight high-resolution network for human pose estimation. arXiv.","DOI":"10.24963\/ijcai.2022\/153"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1141","DOI":"10.1007\/s11263-022-01739-w","article-title":"Vitaev2: Vision transformer advanced by exploring inductive bias for image recognition and beyond","volume":"131","author":"Zhang","year":"2023","journal-title":"Int. J. Comput. Vis."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1007\/s41095-023-0364-2","article-title":"Visual attention network","volume":"9","author":"Guo","year":"2023","journal-title":"Comput. Vis. Media"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Li, J., Su, W., and Wang, Z. (2020, January 7\u201312). Simple pose: Rethinking and improving a bottom-up approach for multi-person pose estimation. Proceedings of the AAAI Conference on Artificial Intelligence, New York, NY, USA.","DOI":"10.1609\/aaai.v34i07.6797"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"7699","DOI":"10.1109\/TCSVT.2024.3377365","article-title":"HF-HRNet: A Simple Hardware Friendly High-Resolution Network","volume":"34","author":"Zhang","year":"2024","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Xiao, B., Wu, H., and Wei, Y. (2018, January 8\u201314). Simple baselines for human pose estimation and tracking. Proceedings of the European Conference on Computer Vision (ECCV), Munich, Germeny.","DOI":"10.1007\/978-3-030-01231-1_29"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Cai, Y., Wang, Z., Luo, Z., Yin, B., Du, A., Wang, H., Zhang, X., Zhou, X., Zhou, E., and Sun, J. (2020, January 23\u201328). Learning delicate local representations for multi-person pose estimation. Proceedings of the Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK. Proceedings, Part III 16.","DOI":"10.1007\/978-3-030-58580-8_27"},{"key":"ref_26","unstructured":"Wang, J., Long, X., Chen, G., Wu, Z., Chen, Z., and Ding, E. (2022). U-HRnet: Delving into improving semantic representation of high resolution network for dense prediction. arXiv."},{"key":"ref_27","unstructured":"Artacho, B., and Savakis, A. (2021). Omnipose: A multi-scale framework for multi-person pose estimation. arXiv."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Yu, C., Xiao, B., Gao, C., Yuan, L., Zhang, L., Sang, N., and Wang, J. (2021, January 20\u201325). Lite-hrnet: A lightweight high-resolution network. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Nashville, TN, USA.","DOI":"10.1109\/CVPR46437.2021.01030"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.Y., and Kweon, I.S. (2018, January 8\u201314). Cbam: Convolutional block attention module. Proceedings of the European Conference on Computer Vision (ECCV), Munich, Germany.","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., and Sun, G. (2018, January 18\u201323). Squeeze-and-excitation networks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"111759","DOI":"10.1109\/ACCESS.2022.3216470","article-title":"Optimized S2E Attention Block based Convolutional Network for Human Pose Estimation","volume":"10","author":"Feng","year":"2022","journal-title":"IEEE Access"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"108159","DOI":"10.1016\/j.patcog.2021.108159","article-title":"Delving deep into spatial pooling for squeeze-and-excitation networks","volume":"121","author":"Jin","year":"2022","journal-title":"Pattern Recognit."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/16\/4\/313\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:15:01Z","timestamp":1760030101000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/16\/4\/313"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,15]]},"references-count":32,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2025,4]]}},"alternative-id":["info16040313"],"URL":"https:\/\/doi.org\/10.3390\/info16040313","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,15]]}}}