{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T00:30:47Z","timestamp":1760488247561,"version":"build-2065373602"},"publisher-location":"New York, NY, USA","reference-count":15,"publisher":"ACM","funder":[{"name":"National Science and Technology Council","award":["NSTC111\u20102222\u2010E\u2010110\u2010006\u2010MY3"],"award-info":[{"award-number":["NSTC111\u20102222\u2010E\u2010110\u2010006\u2010MY3"]}]},{"name":"National Science and Technology Council","award":["NSTC112\u20102628\u2010E\u2010110\u2010001\u2010MY3"],"award-info":[{"award-number":["NSTC112\u20102628\u2010E\u2010110\u2010001\u2010MY3"]}]},{"name":"National Science and Technology Council","award":["NSTC113\u20102634\u2010F\u2010110\u2010001\u2010MBK"],"award-info":[{"award-number":["NSTC113\u20102634\u2010F\u2010110\u2010001\u2010MBK"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,11,28]]},"DOI":"10.1145\/3732437.3732753","type":"proceedings-article","created":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T10:33:54Z","timestamp":1760438034000},"page":"89-95","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["An Effective Vehicle Trajectory Restoration Algorithm Based on Center Trajectory"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-4263-6046","authenticated-orcid":false,"given":"Yung-Hao","family":"Shiau","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6972-6577","authenticated-orcid":false,"given":"Chih-Chieh","family":"Hung","sequence":"additional","affiliation":[{"name":"Department of Management Information Systems, National Chung Hsing University, Taichung, Taiwan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0128-4052","authenticated-orcid":false,"given":"Chun-Wei","family":"Tsai","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan"}]}],"member":"320","published-online":{"date-parts":[[2025,10,14]]},"reference":[{"key":"e_1_3_3_1_2_2","first-page":"392","volume-title":"Proceedings of the IEEE Intelligent Vehicles Symposium","author":"Bas Erhan","year":"2007","unstructured":"Erhan Bas, A\u00a0Murat Tekalp, and F\u00a0Sibel. Salman. 2007. Automatic Vehicle Counting from Video for Traffic Flow Analysis. In Proceedings of the IEEE Intelligent Vehicles Symposium. 392\u2013397."},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2016.7533003"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00934"},{"key":"e_1_3_3_1_5_2","doi-asserted-by":"crossref","unstructured":"Davide Chicco Matthijs\u00a0J Warrens and Giuseppe Jurman. 2021. The coefficient of determination R-squared is more informative than SMAPE MAE MAPE MSE and RMSE in regression analysis evaluation. Peerj Computer Science 7 (2021) e623.","DOI":"10.7717\/peerj-cs.623"},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"crossref","unstructured":"Wenhan Luo Junliang Xing Anton Milan Xiaoqin Zhang Wei Liu and Tae\u00a0Kyun Kim. 2021. Multiple object tracking: A literature review. Artificial Intelligence 293 (2021) 103448.","DOI":"10.1016\/j.artint.2020.103448"},{"key":"e_1_3_3_1_8_2","first-page":"281","volume-title":"Proceedings of Fifth Berkeley Symposium on Mathematical Statistics and Probability","author":"MacQueen J\u00a0B","year":"1967","unstructured":"J\u00a0B MacQueen. 1967. Some methods for classification and analysis of multivariate observations. In Proceedings of Fifth Berkeley Symposium on Mathematical Statistics and Probability. 281\u2013297."},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"crossref","unstructured":"Boris Medina-Salgado Eddy S\u00e1nchez-DelaCruz Pilar Pozos-Parra and Javier\u00a0E Sierra. 2022. Urban traffic flow prediction techniques: A review. Sustainable Computing: Informatics and Systems 35 (2022) 100739.","DOI":"10.1016\/j.suscom.2022.100739"},{"key":"e_1_3_3_1_10_2","volume-title":"The dynamic Hungarian algorithm for the assignment problem with changing costs","author":"Mills-Tettey G\u00a0Ayorkor","year":"2007","unstructured":"G\u00a0Ayorkor Mills-Tettey, Anthony Stentz, and M\u00a0Bernardine Dias. 2007. The dynamic Hungarian algorithm for the assignment problem with changing costs. Tech. Rep., CMU-RI-TR-07-27. Robotics Institute, Pittsburgh, PA, USA."},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.91"},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"crossref","unstructured":"Shaoqing Ren Kaiming He Ross Girshick and Jian Sun. 2016. Faster R-CNN: Towards real-time object detection with region proposal networks. IEEE transactions on pattern analysis and machine intelligence 39 6 (2016) 1137\u20131149.","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"e_1_3_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2017.8296962"},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"crossref","unstructured":"Peng Xie Tianrui Li Jia Liu Shengdong Du Xin Yang and Junbo Zhang. 2020. Urban flow prediction from spatiotemporal data using machine learning: A survey. Information Fusion 59 (2020) 1\u201312.","DOI":"10.1016\/j.inffus.2020.01.002"},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"crossref","unstructured":"Xiaokang Zhang Yan Yan Jing-Hao Xue Yang Hua and Hanzi Wang. 2021. Semantic-aware occlusion-robust network for occluded person Re-identification. IEEE Transactions on Circuits and Systems for Video Technology 31 7 (2021) 2764\u20132778.","DOI":"10.1109\/TCSVT.2020.3033165"},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"crossref","unstructured":"Zhong-Qiu Zhao Peng Zheng Shou-tao Xu and Xindong Wu. Nov. 2019. Object detection with deep learning: A review. IEEE Transactions on Neural Networks and Learning Systems 30 11 (Nov. 2019) 3212\u20133232.","DOI":"10.1109\/TNNLS.2018.2876865"}],"event":{"name":"ICEA 2024: The 2024 International Conference on Intelligent Computing and its Emerging Applicaton","location":"Tokyo Japan","acronym":"ICEA 2024"},"container-title":["Proceedings of the 2024 International Conference on Intelligent Computing and its Emerging Applicaton"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3732437.3732753","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T10:35:38Z","timestamp":1760438138000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3732437.3732753"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,28]]},"references-count":15,"alternative-id":["10.1145\/3732437.3732753","10.1145\/3732437"],"URL":"https:\/\/doi.org\/10.1145\/3732437.3732753","relation":{},"subject":[],"published":{"date-parts":[[2024,11,28]]},"assertion":[{"value":"2025-10-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}