{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,25]],"date-time":"2025-07-25T09:58:28Z","timestamp":1753437508177,"version":"3.37.3"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2022,1,30]],"date-time":"2022-01-30T00:00:00Z","timestamp":1643500800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,30]],"date-time":"2022-01-30T00:00:00Z","timestamp":1643500800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"national natural science foundation of china","doi-asserted-by":"publisher","award":["62072286","61572296"],"award-info":[{"award-number":["62072286","61572296"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"national natural science foundation of china","doi-asserted-by":"publisher","award":["61876100"],"award-info":[{"award-number":["61876100"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimedia Systems"],"published-print":{"date-parts":[[2022,6]]},"DOI":"10.1007\/s00530-022-00895-w","type":"journal-article","created":{"date-parts":[[2022,1,30]],"date-time":"2022-01-30T15:02:17Z","timestamp":1643554937000},"page":"925-937","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Multi-cue multi-hypothesis tracking with re-identification for multi-object tracking"],"prefix":"10.1007","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3691-4942","authenticated-orcid":false,"given":"Wen","family":"Guo","sequence":"first","affiliation":[]},{"given":"Yuelong","family":"Jin","sequence":"additional","affiliation":[]},{"given":"Bin","family":"Shan","sequence":"additional","affiliation":[]},{"given":"Xinmiao","family":"Ding","sequence":"additional","affiliation":[]},{"given":"Minghao","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,30]]},"reference":[{"key":"895_CR1","unstructured":"Luo, W., Xing, J., Milan, A., Zhang, X., Liu, W., Zhao, X., Kim, T.K.: Multiple object tracking: A literature review. arXiv preprint arXiv:1409.7618 (2014)"},{"issue":"6","key":"895_CR2","doi-asserted-by":"publisher","first-page":"843","DOI":"10.1109\/TAC.1979.1102177","volume":"24","author":"D Reid","year":"1979","unstructured":"Reid, D.: An algorithm for tracking multiple targets. IEEE Trans. Autom. Control 24(6), 843\u2013854 (1979)","journal-title":"IEEE Trans. Autom. Control"},{"key":"895_CR3","doi-asserted-by":"crossref","unstructured":"Kim, C., Li, F., Ciptadi, A., Rehg, J.M.: Multiple hypothesis tracking revisited. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 4696\u20134704 (2015)","DOI":"10.1109\/ICCV.2015.533"},{"key":"895_CR4","doi-asserted-by":"crossref","unstructured":"Li, F., Kim, T., Humayun, A., Tsai, D., Rehg, J.M.: Video segmentation by tracking many figure-ground segments. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2192\u20132199 (2013)","DOI":"10.1109\/ICCV.2013.273"},{"key":"895_CR5","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.neucom.2019.11.023","volume":"381","author":"G Ciaparrone","year":"2020","unstructured":"Ciaparrone, G., S\u00e1nchez, F.L., Tabik, S., Troiano, L., Tagliaferri, R., Herrera, F.: Deep learning in video multi-object tracking: A survey. Neurocomputing 381, 61\u201388 (2020)","journal-title":"Neurocomputing"},{"key":"895_CR6","doi-asserted-by":"crossref","unstructured":"Leal-Taixe, L., Pons-Moll, G., Rosenhahn, B.: Branch-and-price global optimization for multi-view multi-target tracking. In: IEEE Conference on Computer Vision and Pattern Recognition, IEEE, pp. 1987\u20131994 (2012)","DOI":"10.1109\/CVPR.2012.6247901"},{"key":"895_CR7","unstructured":"Emami, P., Pardalos, P.M., Elefteriadou, L., Ranka, S.: Machine learning methods for solving assignment problems in multi-target tracking. arXiv preprint arXiv:1802.06897 (2018)"},{"issue":"1","key":"895_CR8","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1109\/TPAMI.2005.1","volume":"27","author":"K Shafique","year":"2005","unstructured":"Shafique, K., Shah, M.: A noniterative greedy algorithm for multiframe point correspondence. IEEE Trans. Pattern Anal. Mach. Intell. 27(1), 51\u201365 (2005)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"895_CR9","doi-asserted-by":"crossref","unstructured":"Shu, G., Dehghan, A., Oreifej, O., Hand, E., Shah, M.: Part-based multiple-person tracking with partial occlusion handling. In: IEEE Conference on Computer Vision and Pattern Recognition, IEEE, pp. 1815\u20131821 (2012)","DOI":"10.1109\/CVPR.2012.6247879"},{"key":"895_CR10","doi-asserted-by":"crossref","unstructured":"Fang, K., Xiang, Y., Li, X., Savarese, S.: Recurrent autoregressive networks for online multi-object tracking. In: IEEE Winter Conference on Applications of Computer Vision (WACV), IEEE, pp. 466\u2013475 (2018)","DOI":"10.1109\/WACV.2018.00057"},{"key":"895_CR11","doi-asserted-by":"crossref","unstructured":"Sadeghian, A., Alahi, A., Savarese, S.: Tracking the untrackable: Learning to track multiple cues with long-term dependencies. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 300\u2013311 (2017)","DOI":"10.1109\/ICCV.2017.41"},{"key":"895_CR12","first-page":"3645","volume":"2017","author":"N Wojke","year":"2017","unstructured":"Wojke, N., Bewley, A., Paulus, D.: Simple online and realtime tracking with a deep association metric. IEEE Int. Conf. Image Process. 2017, 3645\u20133649 (2017)","journal-title":"IEEE Int. Conf. Image Process."},{"key":"895_CR13","doi-asserted-by":"crossref","unstructured":"Chu, Q., Ouyang, W., Li, H., Wang, X., Liu, B., Yu, N.: Online multi-object tracking using cnn-based single object tracker with spatial-temporal attention mechanism. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 4836\u20134845 (2017)","DOI":"10.1109\/ICCV.2017.518"},{"key":"895_CR14","doi-asserted-by":"crossref","unstructured":"Milan, A., Rezatofighi, S.H., Dick, A., Reid, I., Schindler, K.: Online multi-target tracking using recurrent neural networks. In: Thirty-First AAAI Conference on Artificial Intelligence (2017)","DOI":"10.1609\/aaai.v31i1.11194"},{"key":"895_CR15","doi-asserted-by":"crossref","unstructured":"Son, J., Baek, M., Cho, M., Han, B.: Multi-object tracking with quadruplet convolutional neural networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 5620\u20135629 (2017)","DOI":"10.1109\/CVPR.2017.403"},{"key":"895_CR16","first-page":"104","volume":"43","author":"S Sun","year":"2019","unstructured":"Sun, S., Akhtar, N., Song, H., Mian, A.S., Shah, M.: Deep affinity network for multiple object tracking. IEEE Trans. Pattern Anal. Mach. Intell 43, 104\u2013119 (2019)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"895_CR17","unstructured":"Xu, Y., Ban, Y., Alameda-Pineda, X., Horaud, R.: Deepmot: A differentiable framework for training multiple object trackers. arXiv preprint arXiv:1906.06618 (2019)"},{"key":"895_CR18","first-page":"343","volume-title":"European conference on computer vision","author":"AR Zamir","year":"2012","unstructured":"Zamir, A.R., Dehghan, A., Shah, M.: Gmcp-tracker: Global multi-object tracking using generalized minimum clique graphs. In: European conference on computer vision, pp. 343\u2013356. Springer, Berlin (2012)"},{"issue":"2","key":"895_CR19","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1007\/s11263-006-0027-7","volume":"75","author":"B Wu","year":"2007","unstructured":"Wu, B., Nevatia, R.: Detection and tracking of multiple, partially occluded humans by Bayesian combination of edgelet based part detectors. Int. J. Comput. Vision 75(2), 247\u2013266 (2007)","journal-title":"Int. J. Comput. Vision"},{"key":"895_CR20","doi-asserted-by":"crossref","unstructured":"Dehghan, A., Modiri\u00a0Assari, S., Shah, M.: Gmmcp tracker: Globally optimal generalized maximum multi clique problem for multiple object tracking. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4091\u20134099 (2015)","DOI":"10.1109\/CVPR.2015.7299036"},{"issue":"9","key":"895_CR21","doi-asserted-by":"publisher","first-page":"1806","DOI":"10.1109\/TPAMI.2011.21","volume":"33","author":"J Berclaz","year":"2011","unstructured":"Berclaz, J., Fleuret, F., Turetken, E., Fua, P.: Multiple object tracking using k-shortest paths optimization. IEEE Trans. Pattern Anal. Mach. Intell. 33(9), 1806\u20131819 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"895_CR22","first-page":"549","volume-title":"European conference on computer vision","author":"A Robicquet","year":"2016","unstructured":"Robicquet, A., Sadeghian, A., Alahi, A., Savarese, S.: Learning social etiquette: Human trajectory understanding in crowded scenes. In: European conference on computer vision, pp. 549\u2013565. Springer, Berlin (2016)"},{"key":"895_CR23","doi-asserted-by":"crossref","unstructured":"Leal-Taix\u00e9, L., Canton-Ferrer, C., Schindler, K.: Learning by tracking: Siamese cnn for robust target association. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 33\u201340 (2016)","DOI":"10.1109\/CVPRW.2016.59"},{"key":"895_CR24","doi-asserted-by":"crossref","unstructured":"Wang, B., Wang, L., Shuai, B., Zuo, Z., Liu, T., Luk\u00a0Chan, K., Wang, G.: Joint learning of convolutional neural networks and temporally constrained metrics for tracklet association. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 1\u20138 (2016)","DOI":"10.1109\/CVPRW.2016.55"},{"key":"895_CR25","doi-asserted-by":"crossref","unstructured":"Ma, C., Yang, C., Yang, F., Zhuang, Y., Zhang, Z., Jia, H., Xie, X.: Trajectory factory: Tracklet cleaving and re-connection by deep siamese bi-gru for multiple object tracking. In: IEEE International Conference on Multimedia and Expo (ICME), IEEE, pp. 1\u20136 (2018)","DOI":"10.1109\/ICME.2018.8486454"},{"key":"895_CR26","doi-asserted-by":"crossref","unstructured":"Tang, S., Andres, B., Andriluka, M., Schiele, B.: Subgraph decomposition for multi-target tracking. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. (2015) 5033\u20135041","DOI":"10.1109\/CVPR.2015.7299138"},{"key":"895_CR27","first-page":"100","volume-title":"European conference on computer vision","author":"S Tang","year":"2016","unstructured":"Tang, S., Andres, B., Andriluka, M., Schiele, B.: Multi-person tracking by multicut and deep matching. In: European conference on computer vision, pp. 100\u2013111. Springer, Berlin (2016)"},{"key":"895_CR28","doi-asserted-by":"crossref","unstructured":"Schulter, S., Vernaza, P., Choi, W., Chandraker, M.: Deep network flow for multi-object tracking. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6951\u20136960 (2017)","DOI":"10.1109\/CVPR.2017.292"},{"key":"895_CR29","doi-asserted-by":"crossref","unstructured":"Philipp\u00a0Bergmann, Tim\u00a0Meinhardt, L.L.T.: Tracking without bells and whistles. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 941\u2013951 (2019)","DOI":"10.1109\/ICCV.2019.00103"},{"key":"895_CR30","unstructured":"Yihong\u00a0Xu, A.\u00a0sep, Y.B.: How to train your deep multi-object tracker. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6786\u20136795 (2020)"},{"key":"895_CR31","doi-asserted-by":"crossref","unstructured":"Collins, R.T.: Multitarget data association with higher-order motion models. In: IEEE conference on computer vision and pattern recognition, IEEE, pp. 1744\u20131751 (2012)","DOI":"10.1109\/CVPR.2012.6247870"},{"key":"895_CR32","doi-asserted-by":"crossref","unstructured":"Kim, C., Li, F., Rehg, J.M.: Multi-object tracking with neural gating using bilinear lstm. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 200\u2013215 (2018)","DOI":"10.1007\/978-3-030-01237-3_13"},{"key":"895_CR33","doi-asserted-by":"crossref","unstructured":"Davis, J.V., Kulis, B., Jain, P., Sra, S., Dhillon, I.S.: Informationp-theoretic metric learning. In: Proceedings of the 24th International Conference on Machine Learning, pp. 209\u2013216 (2007)","DOI":"10.1145\/1273496.1273523"},{"key":"895_CR34","doi-asserted-by":"crossref","unstructured":"Wojke, N., Bewley, A.: Deep cosine metric learning for person re-identification. In: IEEE winter conference on applications of computer vision (WACV), IEEE, pp. 748\u2013756 (2018)","DOI":"10.1109\/WACV.2018.00087"},{"key":"895_CR35","unstructured":"Blackman, S., Blackman, S.S., Popoli, R.: Design and analysis of modern tracking systems. (1999)"},{"issue":"2","key":"895_CR36","doi-asserted-by":"publisher","first-page":"138","DOI":"10.1109\/34.481539","volume":"18","author":"IJ Cox","year":"1996","unstructured":"Cox, I.J., Hingorani, S.L.: An efficient implementation of reid\u2019s multiple hypothesis tracking algorithm and its evaluation for the purpose of visual tracking. IEEE Trans. Pattern Anal. Mach. Intell. 18(2), 138\u2013150 (1996)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"895_CR37","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1007\/978-3-540-88063-9_15","volume-title":"Optimization and cooperative control strategies","author":"DJ Papageorgiou","year":"2009","unstructured":"Papageorgiou, D.J., Salpukas, M.R.: The maximum weight independent set problem for data association in multiple hypothesis tracking. In: Optimization and cooperative control strategies, pp. 235\u2013255. Springer, Berlin arXiv preprint arXiv:1603.00831(2009)"},{"issue":"15","key":"895_CR38","doi-asserted-by":"publisher","first-page":"2080","DOI":"10.1016\/j.dam.2005.04.010","volume":"154","author":"S Busygin","year":"2006","unstructured":"Busygin, S.: A new trust region technique for the maximum weight clique problem. Discret. Appl. Math. 154(15), 2080\u20132096 (2006)","journal-title":"Discret. Appl. Math."},{"key":"895_CR39","unstructured":"Milan, A., Leal-Taix\u00e9, L., Reid, I., Roth, S., Schindler, K.: Mot16: A benchmark for multi-object tracking. arXiv preprint arXiv:1603.00831 (2016)"},{"key":"895_CR40","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2008\/246309","volume":"2008","author":"K Bernardin","year":"2008","unstructured":"Bernardin, K., Stiefelhagen, R.: Evaluating multiple object tracking performance: the clear mot metrics. EURASIP J. Image Video Process. 2008, 1\u201310 (2008)","journal-title":"EURASIP J. Image Video Process."},{"key":"895_CR41","doi-asserted-by":"crossref","unstructured":"Yang, B., Huang, C., Nevatia, R.: Learning affinities and dependencies for multi-target tracking using a crf model. In: Proceedings of the IEEE International Conference on Computer Vision, IEEE, pp. 1233\u20131240 (2011)","DOI":"10.1109\/CVPR.2011.5995587"},{"key":"895_CR42","doi-asserted-by":"crossref","unstructured":"Bergmann, P., Meinhardt, T., Leal-Taixe, L.: Tracking without bells and whistles. arXiv preprint arxiv190305625v3 (2019)","DOI":"10.1109\/ICCV.2019.00103"},{"key":"895_CR43","doi-asserted-by":"crossref","unstructured":"Chu, P., Fan, H., Tan, C.C., Ling, H.: Online multi-object tracking with instance-aware tracker and dynamic model refreshment. In: IEEE Winter Conference on Applications of Computer Vision (WACV), IEEE, pp. 161\u2013170 (2019)","DOI":"10.1109\/WACV.2019.00023"},{"key":"895_CR44","doi-asserted-by":"crossref","unstructured":"Tang, S., Andriluka, M., Andres, B., Schiele, B.: Multiple people tracking by lifted multicut and person re-identification. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3539\u20133548 (2017)","DOI":"10.1109\/CVPR.2017.394"},{"issue":"12","key":"895_CR45","doi-asserted-by":"publisher","first-page":"3660","DOI":"10.1109\/TCSVT.2018.2881123","volume":"29","author":"H Sheng","year":"2018","unstructured":"Sheng, H., Chen, J., Zhang, Y., Ke, W., Xiong, Z., Yu, J.: Iterative multiple hypothesis tracking with tracklet-level association. IEEE Trans. Circuits Syst. Video Technol. 29(12), 3660\u20133672 (2018)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"895_CR46","doi-asserted-by":"crossref","unstructured":"Xu, J., Cao, Y., Zhang, Z., Hu, H.: Spatial-temporal relation networks for multi-object tracking. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3988\u20133998 (2019)","DOI":"10.1109\/ICCV.2019.00409"},{"key":"895_CR47","doi-asserted-by":"crossref","unstructured":"Chen, L., Ai, H., Shang, C., Zhuang, Z., Bai, B.: Online multi-object tracking with convolutional neural networks. In: IEEE International Conference on Image Processing (ICIP), IEEE, pp. 645\u2013649 (2017)","DOI":"10.1109\/ICIP.2017.8296360"},{"key":"895_CR48","doi-asserted-by":"crossref","unstructured":"Choi, W.: Near-online multi-target tracking with aggregated local flow descriptor. In: Proceedings of the IEEE international conference on computer vision, pp. 3029\u20133037 (2015)","DOI":"10.1109\/ICCV.2015.347"},{"issue":"4","key":"895_CR49","doi-asserted-by":"publisher","first-page":"1011","DOI":"10.1109\/TCSVT.2018.2825679","volume":"29","author":"H Zhou","year":"2018","unstructured":"Zhou, H., Ouyang, W., Cheng, J., Wang, X., Li, H.: Deep continuous conditional random fields with asymmetric inter-object constraints for online multi-object tracking. IEEE Trans. Circuits Syst. Video Technol. 29(4), 1011\u20131022 (2018)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"895_CR50","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.cviu.2016.05.003","volume":"153","author":"M Yang","year":"2016","unstructured":"Yang, M., Jia, Y.: Temporal dynamic appearance modeling for online multi-person tracking. Comput. Vis. Image Underst. 153, 16\u201328 (2016)","journal-title":"Comput. Vis. Image Underst."}],"container-title":["Multimedia Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-022-00895-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00530-022-00895-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-022-00895-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,17]],"date-time":"2024-09-17T16:27:37Z","timestamp":1726590457000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00530-022-00895-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,30]]},"references-count":50,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2022,6]]}},"alternative-id":["895"],"URL":"https:\/\/doi.org\/10.1007\/s00530-022-00895-w","relation":{},"ISSN":["0942-4962","1432-1882"],"issn-type":[{"type":"print","value":"0942-4962"},{"type":"electronic","value":"1432-1882"}],"subject":[],"published":{"date-parts":[[2022,1,30]]},"assertion":[{"value":"21 June 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 January 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 January 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}