{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T08:40:44Z","timestamp":1774600844568,"version":"3.50.1"},"publisher-location":"Cham","reference-count":42,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030012366","type":"print"},{"value":"9783030012373","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-01237-3_13","type":"book-chapter","created":{"date-parts":[[2018,10,6]],"date-time":"2018-10-06T18:42:18Z","timestamp":1538851338000},"page":"208-224","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":164,"title":["Multi-object Tracking with Neural Gating Using Bilinear LSTM"],"prefix":"10.1007","author":[{"given":"Chanho","family":"Kim","sequence":"first","affiliation":[]},{"given":"Fuxin","family":"Li","sequence":"additional","affiliation":[]},{"given":"James M.","family":"Rehg","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,10,7]]},"reference":[{"key":"13_CR1","doi-asserted-by":"crossref","unstructured":"A. Sadeghian, A. Alahi, S.S.: Tracking the untrackable: learning to track multiple cues with long-term dependencies. In: ICCV (2017)","DOI":"10.1109\/ICCV.2017.41"},{"key":"13_CR2","doi-asserted-by":"crossref","unstructured":"Andriluka, M., Roth, S., Schiele, B.: People-tracking-by-detection and people-detection-by-tracking. In: CVPR (2008)","DOI":"10.1109\/CVPR.2008.4587583"},{"key":"13_CR3","doi-asserted-by":"publisher","first-page":"595","DOI":"10.1109\/TPAMI.2017.2691769","volume":"40","author":"SH Bae","year":"2018","unstructured":"Bae, S.H., Yoon, K.J.: Confidence-based data association and discriminative deep appearance learning for robust online multi-object tracking. IEEE Trans. Pattern Anal. Mach. Intell. 40, 595\u2013610 (2018)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"13_CR4","first-page":"246309","volume":"2008","author":"K Bernardin","year":"2008","unstructured":"Bernardin, K., Stiefelhagen, R.: Evaluating multiple object tracking performance the CLEAR MOT metrics. Image Video Process. 2008, 246309 (2008)","journal-title":"Image Video Process."},{"issue":"1","key":"13_CR5","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1109\/MAES.2004.1263228","volume":"19","author":"S Blackman","year":"2004","unstructured":"Blackman, S.: Multiple hypothesis tracking for multiple target tracking. Aerosp. Electron. Syst. Mag. 19(1), 5\u201318 (2004)","journal-title":"Aerosp. Electron. Syst. Mag."},{"key":"13_CR6","doi-asserted-by":"crossref","unstructured":"Chen, J., Sheng, H., Zhang, Y., Xiong, Z.: Enhancing detection model for multiple hypothesis tracking. In: CVPR Workshops (2017)","DOI":"10.1109\/CVPRW.2017.266"},{"key":"13_CR7","doi-asserted-by":"crossref","unstructured":"Choi, W.: Near-online multi-target tracking with aggregated local flow descriptor. In: ICCV (2015)","DOI":"10.1109\/ICCV.2015.347"},{"key":"13_CR8","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: ICCV (2017)","DOI":"10.1109\/ICCV.2017.518"},{"key":"13_CR9","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, 138\u2013150 (1996)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"13_CR10","doi-asserted-by":"crossref","unstructured":"Ess, A., Leibe, B., Schindler, K., van Gool, L.: A mobile vision system for robust multi-person tracking. In: CVPR (2008)","DOI":"10.1109\/CVPR.2008.4587581"},{"key":"13_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"774","DOI":"10.1007\/978-3-319-46484-8_47","volume-title":"Computer Vision \u2013 ECCV 2016","author":"L Fagot-Bouquet","year":"2016","unstructured":"Fagot-Bouquet, L., Audigier, R., Dhome, Y., Lerasle, F.: Improving multi-frame data association with sparse representations for robust near-online multi-object tracking. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9912, pp. 774\u2013790. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46484-8_47"},{"key":"13_CR12","doi-asserted-by":"crossref","unstructured":"Fang, K., Xiang, Y., Li, X., Savarese, S.: Recurrent autoregressive networks for online multi-object tracking. In: WACV (2018)","DOI":"10.1109\/WACV.2018.00057"},{"issue":"9","key":"13_CR13","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1109\/TPAMI.2009.167","volume":"32","author":"PF Felzenszwalb","year":"2010","unstructured":"Felzenszwalb, P.F., Girshick, R.B., McAllester, D., Ramanan, D.: Object detection with discriminatively trained part based models. IEEE Trans. Pattern Anal. Mach. Intell. 32(9), 1627\u20131645 (2010)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"13_CR14","doi-asserted-by":"publisher","first-page":"14764","DOI":"10.1109\/ACCESS.2018.2816805","volume":"6","author":"Z Fu","year":"2018","unstructured":"Fu, Z., Feng, P., Angelini, F., Chambers, J.A., Naqvi, S.M.: Particle phd filter based multiple human tracking using online group-structured dictionary learning. IEEE Access 6, 14764\u201314778 (2018)","journal-title":"IEEE Access"},{"key":"13_CR15","doi-asserted-by":"crossref","unstructured":"Geiger, A., Lenz, P., Urtasun, R.: Are we ready for autonomous driving? the KITTI vision benchmark suite. In: CVPR (2012)","DOI":"10.1109\/CVPR.2012.6248074"},{"key":"13_CR16","doi-asserted-by":"crossref","unstructured":"Girshick, R., Donahue, J., Darrell, T., Malik, J.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: CVPR (2014)","DOI":"10.1109\/CVPR.2014.81"},{"key":"13_CR17","volume-title":"Deep Learning","author":"I Goodfellow","year":"2016","unstructured":"Goodfellow, I., Bengio, Y., Courville, A., Bengio, Y.: Deep Learning, vol. 1. MIT Press, Cambridge (2016)"},{"issue":"2","key":"13_CR18","doi-asserted-by":"publisher","first-page":"788","DOI":"10.1109\/LRA.2018.2792152","volume":"3","author":"D Gordon","year":"2018","unstructured":"Gordon, D., Farhadi, A., Fox, D.: Re3: Real-time recurrent regression networks for visual tracking of generic objects. IEEE Robot. Autom. Lett. 3(2), 788\u2013795 (2018)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"13_CR19","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"13_CR20","doi-asserted-by":"crossref","unstructured":"Henschel, R., Leal-Taix\u00e9, L., Cremers, D., Rosenhahn, B.: Fusion of head and full-body detectors for multi-object tracking. In: CVPR Workshops (2018)","DOI":"10.1109\/CVPRW.2018.00192"},{"key":"13_CR21","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9, 1735\u20131780 (1997)","journal-title":"Neural Comput."},{"key":"13_CR22","doi-asserted-by":"crossref","unstructured":"Hong Yoon, J., Lee, C.R., Yang, M.H., Yoon, K.J.: Online multi-object tracking via structural constraint event aggregation. In: CVPR. pp. 1392\u20131400 (2016)","DOI":"10.1109\/CVPR.2016.155"},{"key":"13_CR23","unstructured":"Keuper, M., Tang, S., Yu, Z., Andres, B., Brox, T., Schiele, B.: A multi-cut formulation for joint segmentation and tracking of multiple objects. arXiv:1607.06317 (2016)"},{"key":"13_CR24","doi-asserted-by":"crossref","unstructured":"Kim, C., Li, F., Ciptadi, A., Rehg, J.: Multiple hypothesis tracking revisited. In: ICCV (2015)","DOI":"10.1109\/ICCV.2015.533"},{"key":"13_CR25","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. In: ICLR (2015)"},{"key":"13_CR26","doi-asserted-by":"crossref","unstructured":"Leal-Taix\u00e9, L., Canton-Ferrer, C., Schindler, K.: Learning by tracking: siamese CNN for robust target association. In: CVPR Workshops (2016)","DOI":"10.1109\/CVPRW.2016.59"},{"key":"13_CR27","unstructured":"Leal-Taix\u00e9, L., Milan, A., Reid, I., Roth, S., Schindler, K.: MOTChallenge 2015: Towards a benchmark for multi-target tracking. arXiv:1504.01942 (2015)"},{"key":"13_CR28","unstructured":"Leal-Taixe, L., Milan, A., Schindler, K., Cremers, D., Reid, I., Roth, S.: Tracking the trackers: an analysis of the state of the art in multiple object tracking. arXiv:1704.02781 (2017)"},{"key":"13_CR29","doi-asserted-by":"crossref","unstructured":"Levinkov, E., et al.: Joint graph decomposition & node labeling: problem, algorithms, applications. In: CVPR (2017)","DOI":"10.1109\/CVPR.2017.206"},{"key":"13_CR30","doi-asserted-by":"crossref","unstructured":"Li, W., Zhao, R., Xiao, T., Wang, X.: DeeReID: deep filter pairing neural network for person re-identification. In: CVPR (2014)","DOI":"10.1109\/CVPR.2014.27"},{"key":"13_CR31","unstructured":"Long, C., Haizhou, A., Zijie, Z., Chong, S.: Real-time multiple people tracking with deeply learned candidate selection and person re-identification. In: ICME (2018)"},{"key":"13_CR32","unstructured":"Milan, A., Leal-Taix\u00e9, L., Reid, I., Roth, S., Schindler, K.: MOT16: A benchmark for multi-object tracking. arXiv:1603.00831 (2016)"},{"key":"13_CR33","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: AAAI (2017)","DOI":"10.1609\/aaai.v31i1.11194"},{"key":"13_CR34","series-title":"LNCIS","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: Hirsch, M.J., Commander, C.W., Pardalos, P.M., Murphey, R. (eds.) Optimization and Cooperative Control Strategies. LNCIS, vol. 381, pp. 235\u2013255. Springer, Heidelberg (2009)"},{"key":"13_CR35","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. In: NIPS (2015)"},{"key":"13_CR36","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1007\/978-3-319-48881-3_2","volume-title":"Computer Vision \u2013 ECCV 2016 Workshops","author":"E Ristani","year":"2016","unstructured":"Ristani, E., Solera, F., Zou, R., Cucchiara, R., Tomasi, C.: Performance measures and a data set for\u00a0multi-target, multi-camera tracking. In: Hua, G., J\u00e9gou, H. (eds.) ECCV 2016. LNCS, vol. 9914, pp. 17\u201335. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-48881-3_2"},{"key":"13_CR37","doi-asserted-by":"crossref","unstructured":"Son, J., Baek, M., Cho, M., Han, B.: Multi-object tracking with quadruplet convolutional neural networks. In: CVPR (2017)","DOI":"10.1109\/CVPR.2017.403"},{"key":"13_CR38","doi-asserted-by":"crossref","unstructured":"Tang, S., Andriluka, M., Andres, B., Schiele, B.: Multiple people tracking with lifted multicut and person re-identification. In: CVPR (2017)","DOI":"10.1109\/CVPR.2017.394"},{"key":"13_CR39","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1007\/978-3-319-48881-3_8","volume-title":"Computer Vision \u2013 ECCV 2016 Workshops","author":"S Tang","year":"2016","unstructured":"Tang, S., Andres, B., Andriluka, M., Schiele, B.: Multi-person Tracking by multicut and deep matching. In: Hua, G., J\u00e9gou, H. (eds.) ECCV 2016. LNCS, vol. 9914, pp. 100\u2013111. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-48881-3_8"},{"key":"13_CR40","doi-asserted-by":"crossref","unstructured":"Yang, F., Choi, W., Lin, Y.: Exploit all the layers: Fast and accurate CNN object detector with scale dependent pooling and cascaded rejection classifiers. In: CVPR (2016)","DOI":"10.1109\/CVPR.2016.234"},{"key":"13_CR41","doi-asserted-by":"crossref","unstructured":"Yang, T., Chan, A.B.: Recurrent filter learning for visual tracking. arXiv:1708.03874 (2017)","DOI":"10.1109\/ICCVW.2017.235"},{"key":"13_CR42","doi-asserted-by":"crossref","unstructured":"Zheng, L., Shen, L., Tian, L., Wang, S., Wang, J., Tian, Q.: Scalable person re-identification: a benchmark. In: ICCV (2015)","DOI":"10.1109\/ICCV.2015.133"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2018"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-01237-3_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,6]],"date-time":"2022-10-06T00:05:13Z","timestamp":1665014713000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-01237-3_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030012366","9783030012373"],"references-count":42,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-01237-3_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"7 October 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Munich","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2018.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}