{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T00:19:11Z","timestamp":1783556351068,"version":"3.55.0"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032222602","type":"print"},{"value":"9783032222619","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-22261-9_33","type":"book-chapter","created":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T00:10:25Z","timestamp":1783555825000},"page":"411-423","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["MOT_FCG++: Enhanced Representation of\u00a0Spatio-Temporal Motion and\u00a0Appearance Features"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-8494-4569","authenticated-orcid":false,"given":"Yanzhao","family":"Fang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1045-9467","authenticated-orcid":false,"given":"Jun","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4339-5028","authenticated-orcid":false,"given":"Yu","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5094-7647","authenticated-orcid":false,"given":"Ting","family":"Dai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,2]]},"reference":[{"key":"33_CR1","doi-asserted-by":"crossref","unstructured":"Bergmann, P., Meinhardt, T., Leal-Taixe, L.: Tracking without bells and whistles. IEEE (2019)","DOI":"10.1109\/ICCV.2019.00103"},{"key":"33_CR2","doi-asserted-by":"crossref","unstructured":"Bewley, A., Ge, Z., Ott, L., Ramos, F., Upcroft, B.: Simple online and realtime tracking. In: 2016 IEEE International Conference on Image Processing (ICIP), pp. 3464\u20133468. IEEE (2016)","DOI":"10.1109\/ICIP.2016.7533003"},{"key":"33_CR3","unstructured":"Brown, R.G., Hwang, P.Y.: Introduction to random signals and applied kalman filtering: with matlab exercises and solutions. Introduction to Random Signals and Applied Kalman Filtering: with MATLAB Exercises and Solutions (1997)"},{"key":"33_CR4","doi-asserted-by":"crossref","unstructured":"Cao, J., Pang, J., Weng, X., Khirodkar, R., Kitani, K.: Observation-centric sort: rethinking sort for robust multi-object tracking. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9686\u20139696 (2023)","DOI":"10.1109\/CVPR52729.2023.00934"},{"key":"33_CR5","doi-asserted-by":"crossref","unstructured":"Cao, J., Weng, X., Khirodkar, R., Pang, J., Kitani, K.: Observation-centric sort: rethinking sort for robust multi-object tracking (2022)","DOI":"10.1109\/CVPR52729.2023.00934"},{"key":"33_CR6","doi-asserted-by":"crossref","unstructured":"Chen, L., Ai, H., Zhuang, Z., Shang, C.: Real-time multiple people tracking with deeply learned candidate selection and person re-identification. In: IEEE International Conference on Multimedia & Expo, pp.\u00a01\u20136 (2018)","DOI":"10.1109\/ICME.2018.8486597"},{"key":"33_CR7","unstructured":"Dendorfer, P., et al.: Mot20: a benchmark for multi object tracking in crowded scenes (2020)"},{"key":"33_CR8","doi-asserted-by":"crossref","unstructured":"Du, Y., et al.: Strongsort: make deepsort great again. IEEE Trans. Multimedia 25, 8725\u20138737 (2023)","DOI":"10.1109\/TMM.2023.3240881"},{"key":"33_CR9","unstructured":"Ge, Z., Liu, S., Wang, F., Li, Z., Sun, J.: Yolox: exceeding yolo series in 2021. arXiv e-prints (2021)"},{"key":"33_CR10","unstructured":"Girbau, A., Marqu\u00e9s, F., Satoh, S.: Multiple object tracking from appearance by hierarchically clustering tracklets. arXiv preprint arXiv:2210.03355 (2022)"},{"key":"33_CR11","doi-asserted-by":"crossref","unstructured":"He, L., Liao, X., Liu, W., Liu, X., Cheng, P., Mei, T.: Fastreid: a pytorch toolbox for general instance re-identification. In: Proceedings of the 31st ACM International Conference on Multimedia, pp. 9664\u20139667. MM \u201923, Association for Computing Machinery (2023)","DOI":"10.1145\/3581783.3613460"},{"key":"33_CR12","doi-asserted-by":"crossref","unstructured":"Hibbert, D.: Unweighted pair group method with arithmetic mean (UPGMA). IUPAC Stand Online 10 (2017)","DOI":"10.1515\/iupac.88.0132"},{"key":"33_CR13","doi-asserted-by":"crossref","unstructured":"Keni, B., Rainer, S.: Evaluating multiple object tracking performance: the clear mot metrics. EURASIP J. Image Video Process. 2008(1) (2008)","DOI":"10.1155\/2008\/246309"},{"key":"33_CR14","unstructured":"Krhenb\u00fchl, P., Koltun, V., Zhou, X.: Tracking objects as points. In: European Conference on Computer Vision (2020)"},{"key":"33_CR15","doi-asserted-by":"crossref","unstructured":"Luiten, JonathonOsep, e.a.: Hota: a higher order metric for evaluating multi-object tracking. Int. J. Comput. Vision 129(2) (2021)","DOI":"10.1007\/s11263-020-01375-2"},{"key":"33_CR16","doi-asserted-by":"crossref","unstructured":"Meinhardt, T., Kirillov, A., Leal-Taixe, L., Feichtenhofer, C.: Trackformer: multi-object tracking with transformers (2021)","DOI":"10.1109\/CVPR52688.2022.00864"},{"key":"33_CR17","unstructured":"Milan, A., Leal-Taixe, L., Reid, I., Roth, S., Schindler, K.: Mot16: a benchmark for multi-object tracking (2016)"},{"issue":"6","key":"33_CR18","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2017","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans. Patt. Anal. Mach. Intell. 39(6), 1137\u20131149 (2017)","journal-title":"IEEE Trans. Patt. Anal. Mach. Intell."},{"key":"33_CR19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-48881-3_2","volume-title":"Performance measures and a data set for multi-target, multi-camera tracking","author":"E Ristani","year":"2016","unstructured":"Ristani, E., Solera, F., Zou, R.S., Cucchiara, R., Tomasi, C.: Performance measures and a data set for multi-target, multi-camera tracking. Springer, Cham (2016)"},{"key":"33_CR20","unstructured":"Sun, P., et al.: Dancetrack: multi-object tracking in uniform appearance and diverse motion. IEEE"},{"key":"33_CR21","unstructured":"Sun, P., Jiang, Y., Zhang, R., Xie, E., Luo, P.: Transtrack: multiple-object tracking with transformer (2020)"},{"key":"33_CR22","unstructured":"Vaswani, A., et al.: Attention is all you need. arXiv (2017)"},{"key":"33_CR23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58621-8_7","volume-title":"Towards real-time multi-object tracking","author":"Z Wang","year":"2020","unstructured":"Wang, Z., Zheng, L., Liu, Y., Li, Y., Wang, S.: Towards real-time multi-object tracking. Springer, Cham (2020)"},{"key":"33_CR24","doi-asserted-by":"crossref","unstructured":"Wojke, N., Bewley, A., Paulus, D.: Simple online and realtime tracking with a deep association metric. IEEE (2017)","DOI":"10.1109\/ICIP.2017.8296962"},{"key":"33_CR25","doi-asserted-by":"crossref","unstructured":"Yang, M., et al.: Hybrid-sort: weak cues matter for online multi-object tracking. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol.\u00a038, pp. 6504\u20136512 (2024)","DOI":"10.1609\/aaai.v38i7.28471"},{"key":"33_CR26","doi-asserted-by":"crossref","unstructured":"Zhang, Y., et al.: Bytetrack: multi-object tracking by associating every detection box (2022)","DOI":"10.1007\/978-3-031-20047-2_1"},{"key":"33_CR27","doi-asserted-by":"crossref","unstructured":"Zheng, L., Shen, L., Tian, L., Wang, S., Tian, Q.: Scalable person re-identification: a benchmark. In: 2015 IEEE International Conference on Computer Vision (ICCV) (2015)","DOI":"10.1109\/ICCV.2015.133"}],"container-title":["Lecture Notes in Computer Science","Advances in Computer Graphics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-22261-9_33","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T00:10:27Z","timestamp":1783555827000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-22261-9_33"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032222602","9783032222619"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-22261-9_33","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"2 June 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CGI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Computer Graphics International Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hong Kong","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"42","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cgi2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.cgs-network.org\/cgi25","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}