{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T16:00:22Z","timestamp":1784995222547,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":36,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,9,21]],"date-time":"2023-09-21T00:00:00Z","timestamp":1695254400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1831795"],"award-info":[{"award-number":["1831795"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,9,21]]},"DOI":"10.1145\/3615834.3615844","type":"proceedings-article","created":{"date-parts":[[2023,10,11]],"date-time":"2023-10-11T22:45:48Z","timestamp":1697064348000},"page":"1-9","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Understanding the Challenges and Opportunities of Pose-based Anomaly Detection"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7749-9047","authenticated-orcid":false,"given":"Ghazal","family":"Alinezhad Noghre","sequence":"first","affiliation":[{"name":"University of North Carolina at Charlotte, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1366-1919","authenticated-orcid":false,"given":"Armin","family":"Danesh Pazho","sequence":"additional","affiliation":[{"name":"University of North Carolina at Charlotte, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-9922-6041","authenticated-orcid":false,"given":"Vinit","family":"Katariya","sequence":"additional","affiliation":[{"name":"University of North Carolina at Charlotte, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5420-1121","authenticated-orcid":false,"given":"Hamed","family":"Tabkhi","sequence":"additional","affiliation":[{"name":"University of North Carolina at Charlotte, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,10,11]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01951"},{"key":"e_1_3_2_1_2_1","volume-title":"arXiv preprint arXiv:2212.12936","author":"Ardabili Babak\u00a0Rahimi","year":"2022","unstructured":"Babak\u00a0Rahimi Ardabili, Armin\u00a0Danesh Pazho, Ghazal\u00a0Alinezhad Noghre, Christopher Neff, Arun Ravindran, and Hamed Tabkhi. 2022. Understanding Ethics, Privacy, and Regulations in Smart Video Surveillance for Public Safety. arXiv preprint arXiv:2212.12936 (2022)."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/AVSS.2019.8909844"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00309"},{"key":"e_1_3_2_1_5_1","volume-title":"AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time","author":"Fang Hao-Shu","year":"2022","unstructured":"Hao-Shu Fang, Jiefeng Li, Hongyang Tang, Chao Xu, Haoyi Zhu, Yuliang Xiu, Yong-Lu Li, and Cewu Lu. 2022. AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time. IEEE Transactions on Pattern Analysis and Machine Intelligence (2022)."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108232"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","unstructured":"Or Hirschorn and Shai Avidan. 2022. Normalizing Flows for Human Pose Anomaly Detection. https:\/\/doi.org\/10.48550\/ARXIV.2211.10946","DOI":"10.48550\/ARXIV.2211.10946"},{"key":"e_1_3_2_1_8_1","volume-title":"Normalizing Flows for Human Pose Anomaly Detection. arXiv preprint arXiv:2211.10946","author":"Hirschorn Or","year":"2022","unstructured":"Or Hirschorn and Shai Avidan. 2022. Normalizing Flows for Human Pose Anomaly Detection. arXiv preprint arXiv:2211.10946 (2022)."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3172015"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.3390\/electronics11193105"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.12.023"},{"key":"e_1_3_2_1_12_1","volume-title":"Anomaly detection and localization in crowded scenes","author":"Li Weixin","year":"2013","unstructured":"Weixin Li, Vijay Mahadevan, and Nuno Vasconcelos. 2013. Anomaly detection and localization in crowded scenes. IEEE transactions on pattern analysis and machine intelligence 36, 1 (2013), 18\u201332."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/MITS.2021.3049404"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.3390\/app12010004"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.optlaseng.2020.106324"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2021.101471"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.45"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.12.148"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2944377"},{"key":"e_1_3_2_1_20_1","unstructured":"Yunqian Ma and Haibo He. 2013. Imbalanced learning: foundations algorithms and applications. (2013)."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01055"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01227"},{"key":"e_1_3_2_1_23_1","volume-title":"Pishgu: Universal Path Prediction Architecture through Graph Isomorphism and Attentive Convolution. arXiv preprint arXiv:2210.08057","author":"Noghre Ghazal\u00a0Alinezhad","year":"2022","unstructured":"Ghazal\u00a0Alinezhad Noghre, Vinit Katariya, Armin\u00a0Danesh Pazho, Christopher Neff, and Hamed Tabkhi. 2022. Pishgu: Universal Path Prediction Architecture through Graph Isomorphism and Attentive Convolution. arXiv preprint arXiv:2210.08057 (2022)."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13735-022-00227-8"},{"key":"e_1_3_2_1_25_1","volume-title":"Ancilia: Scalable Intelligent Video Surveillance for the Artificial Intelligence of Things. arXiv preprint arXiv:2301.03561","author":"Pazho Armin\u00a0Danesh","year":"2023","unstructured":"Armin\u00a0Danesh Pazho, Christopher Neff, Ghazal\u00a0Alinezhad Noghre, Babak\u00a0Rahimi Ardabili, Shanle Yao, Mohammadreza Baharani, and Hamed Tabkhi. 2023. Ancilia: Scalable Intelligent Video Surveillance for the Artificial Intelligence of Things. arXiv preprint arXiv:2301.03561 (2023)."},{"key":"e_1_3_2_1_26_1","volume-title":"CHAD: Charlotte Anomaly Dataset. arXiv preprint arXiv:2212.09258","author":"Pazho Armin\u00a0Danesh","year":"2022","unstructured":"Armin\u00a0Danesh Pazho, Ghazal\u00a0Alinezhad Noghre, Babak\u00a0Rahimi Ardabili, Christopher Neff, and Hamed Tabkhi. 2022. CHAD: Charlotte Anomaly Dataset. arXiv preprint arXiv:2212.09258 (2022)."},{"key":"e_1_3_2_1_27_1","volume-title":"A survey on deep learning-based real-time crowd anomaly detection for secure distributed video surveillance. Personal and Ubiquitous Computing","author":"Rezaee Khosro","year":"2021","unstructured":"Khosro Rezaee, Sara\u00a0Mohammad Rezakhani, Mohammad\u00a0R Khosravi, and Mohammad\u00a0Kazem Moghimi. 2021. A survey on deep learning-based real-time crowd anomaly detection for secure distributed video surveillance. Personal and Ubiquitous Computing (2021), 1\u201317."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV45572.2020.9093633"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0118432"},{"key":"e_1_3_2_1_30_1","volume-title":"Proceedings, Part XVIII 16","author":"Salzmann Tim","year":"2020","unstructured":"Tim Salzmann, Boris Ivanovic, Punarjay Chakravarty, and Marco Pavone. 2020. Trajectron++: Dynamically-feasible trajectory forecasting with heterogeneous data. In Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part XVIII 16. Springer, 683\u2013700."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3385809"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00678"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00678"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00493"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19778-9_42"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01433"}],"event":{"name":"iWOAR 2023: 8th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence","location":"L\u00fcbeck Germany","acronym":"iWOAR 2023"},"container-title":["Proceedings of the 8th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3615834.3615844","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3615834.3615844","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3615834.3615844","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:10:17Z","timestamp":1750295417000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3615834.3615844"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,21]]},"references-count":36,"alternative-id":["10.1145\/3615834.3615844","10.1145\/3615834"],"URL":"https:\/\/doi.org\/10.1145\/3615834.3615844","relation":{},"subject":[],"published":{"date-parts":[[2023,9,21]]},"assertion":[{"value":"2023-10-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}