{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T16:13:39Z","timestamp":1780676019789,"version":"3.54.1"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2021,2,14]],"date-time":"2021-02-14T00:00:00Z","timestamp":1613260800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,2,14]],"date-time":"2021-02-14T00:00:00Z","timestamp":1613260800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["No.11774031"],"award-info":[{"award-number":["No.11774031"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"the Winter Olympics key project Technology Fund","award":["2018YFF0300804"],"award-info":[{"award-number":["2018YFF0300804"]}]},{"name":"Beijing Science and Technology Project","award":["No.Z181100005918002"],"award-info":[{"award-number":["No.Z181100005918002"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2021,10]]},"DOI":"10.1007\/s11760-021-01867-9","type":"journal-article","created":{"date-parts":[[2021,2,18]],"date-time":"2021-02-18T00:19:16Z","timestamp":1613607556000},"page":"1369-1377","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["High-speed moving target tracking of multi-camera system with overlapped field of view"],"prefix":"10.1007","volume":"15","author":[{"given":"Mi","family":"Yan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuejin","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8504-1335","authenticated-orcid":false,"given":"Ming","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingqin","family":"Kong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liquan","family":"Dong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,2,14]]},"reference":[{"key":"1867_CR1","doi-asserted-by":"crossref","unstructured":"Jodoin, J.P., Bilodeau, G.A., Saunier, N.: Urban tracker: multiple object tracking in urban mixed traffic. In IEEE winter conference on applications of computer vision, Steamboat Springs, CO, USA, March 24\u201326 (2014)","DOI":"10.1109\/WACV.2014.6836010"},{"key":"1867_CR2","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Zeng, C., Liang, H., et al.: A visual target tracking algorithm based on improved Kernelized Correlation Filters. In IEEE international conference on mechatronics and automation (2016)","DOI":"10.1109\/ICMA.2016.7558560"},{"issue":"8","key":"1867_CR3","doi-asserted-by":"publisher","first-page":"1064","DOI":"10.1109\/TPAMI.2004.53","volume":"26","author":"S Avidan","year":"2004","unstructured":"Avidan, S.: Support Vector Tracking. PAMI 26(8), 1064\u20131072 (2004)","journal-title":"PAMI"},{"issue":"3","key":"1867_CR4","doi-asserted-by":"publisher","first-page":"653","DOI":"10.1109\/TPAMI.2012.138","volume":"35","author":"W-S Zheng","year":"2013","unstructured":"Zheng, W.-S., Gong, S., Xiang, T.: Reidentification by relative distance comparison. IEEE Trans. Pattern Anal. Mach. Intell. 35(3), 653\u2013668 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"2","key":"1867_CR5","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1016\/j.infrared.2010.04.002","volume":"53","author":"X Wang","year":"2010","unstructured":"Wang, X., Tang, Z.M.: Modified particle filter-based infrared pedestrian tracking. Infrared Phys. Technol. 53(2), 280\u2013287 (2010)","journal-title":"Infrared Phys. Technol."},{"issue":"18","key":"1867_CR6","doi-asserted-by":"publisher","first-page":"1720","DOI":"10.1016\/j.ijleo.2015.04.071","volume":"126","author":"X Cui","year":"2015","unstructured":"Cui, X., Wu, Q., Zhou, J.: Online fragments-based scale invariant electro-optic tracking with SIFT. Int. J. Light Electr. Opt. 126(18), 1720\u20131725 (2015)","journal-title":"Int. J. Light Electr. Opt."},{"issue":"10","key":"1867_CR7","doi-asserted-by":"publisher","first-page":"1355","DOI":"10.1109\/TPAMI.2003.1233912","volume":"25","author":"S Khan","year":"2003","unstructured":"Khan, S., Shah, M.: Consistent labeling of tracked objects in multipe cameras with overlapping fields of view. IEEE Trans. Pattern Anal. Mach. Intell. 25(10), 1355\u20131360 (2003)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"11","key":"1867_CR8","first-page":"376","volume":"40","author":"LN Gaxiola","year":"2015","unstructured":"Gaxiola, L.N., Diazramirez, V.H., Tapia, J.J.: Performance evaluation of correlation filters for target tracking. J. Bacteriol. 40(11), 376\u2013379 (2015)","journal-title":"J. Bacteriol."},{"key":"1867_CR9","doi-asserted-by":"crossref","unstructured":"Bolme, D.S., Beveridge, J. R., Draper, B. A.: Visual object tracking using adaptive correlation filters. In The twenty-third ieee conference on computer vision and pattern recognition. IEEE (2010)","DOI":"10.1109\/CVPR.2010.5539960"},{"issue":"7","key":"1867_CR10","doi-asserted-by":"publisher","first-page":"1567","DOI":"10.1007\/s11760-014-0612-0","volume":"9","author":"A Ali","year":"2015","unstructured":"Ali, A., Jalil, A., Ahmed, J.: Correlation, Kalman filter and adaptive fast mean shift based heuristic approach for robust visual tracking. SIViP 9(7), 1567\u20131585 (2015)","journal-title":"SIViP"},{"key":"1867_CR11","unstructured":"Bertinetto, L., Valmadre, J., Henriques, J.F.: Fully-convolutional Siamese networks for object tracking. In: IEEE International Conference on Computer Vision, pp. 3119\u20133127 (2015)"},{"key":"1867_CR12","doi-asserted-by":"crossref","unstructured":"Tao, R., Gavves E., Smeulders, A.W.: Siamese instance search for tracking. In IEEE Conference on Computer Vision and Pattern Recognition (2016)","DOI":"10.1109\/CVPR.2016.158"},{"key":"1867_CR13","doi-asserted-by":"crossref","unstructured":"Nam, H., Han, B.: Learning Multi-Domain Convolutional Neural Networks for Visual Tracking. In CVPR (2016)","DOI":"10.1109\/CVPR.2016.465"},{"key":"1867_CR14","doi-asserted-by":"crossref","unstructured":"Zhu, Z., Wang, Q., Li, B., Wu, W., Yan, J., Hu W.: Distractor-aware siamese networks for visual object tracking. In European conference on computer vision (2018)","DOI":"10.1007\/978-3-030-01240-3_7"},{"key":"1867_CR15","doi-asserted-by":"crossref","unstructured":"Li, B., Yan, J., Wu, W., Zhu, Z., Hu, X.: High performance visual tracking with siamese region proposal network. In IEEE conference on computer vision and pattern recognition (2018)","DOI":"10.1109\/CVPR.2018.00935"},{"key":"1867_CR16","unstructured":"Luo, He, C., Tian, X., Zeng, W.: Towards a better match in siamese network based visual object tracker. In European conference on computer vision workshops (2018)"},{"key":"1867_CR17","doi-asserted-by":"crossref","unstructured":"Bertinetto, L., Valmadre, J., Henriques, J.F., Vedaldi A., Torr P. H.: Fully-convolutional siamese networks for object tracking. In European conference on computer vision workshops (2016)","DOI":"10.1007\/978-3-319-48881-3_56"},{"issue":"2","key":"1867_CR18","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1109\/TVCG.2006.39","volume":"12","author":"P Sereda","year":"2006","unstructured":"Sereda, P., Vilanova, A., Serlie, I.W.O.: Visualization of boundaries in volumetric data sets using LH histograms. IEEE Trans. Visual Comput. Graphics 12(2), 208\u2013218 (2006)","journal-title":"IEEE Trans. Visual Comput. Graphics"},{"key":"1867_CR19","doi-asserted-by":"crossref","unstructured":"Stark, M., Schiele, B.: How good are local features for classes of geometric objects. In International conference on computer vision. IEEE (2008)","DOI":"10.1109\/ICCV.2007.4408878"},{"key":"1867_CR20","unstructured":"Redmon, J., Farhadi, A.:YOLOv3: An incremental improvement (2018)"},{"key":"1867_CR21","unstructured":"Roettger, S., Bauer, M., Stamminger, M.: Spatialized transfer functions. In: Proceedings of the Seventh Joint Eurograph. IEEE VGTC Symposium on Visualization. pp. 271\u2013278 (2005)"},{"key":"1867_CR22","doi-asserted-by":"crossref","unstructured":"Bolme, D.S., Beveridge, J.R., Draper, B.A., Lui, Y.M.: Visual object tracking using adaptive correlation filters. In: Proceedings of IEEE conference on computer vision and pattern recognition (2010)","DOI":"10.1109\/CVPR.2010.5539960"},{"key":"1867_CR23","doi-asserted-by":"crossref","unstructured":"Henriques, J.F., Caseiro, R., Martins, P., Batista, J.: Exploiting the circulant structure of tracking-by-detection with kernels.In Proceedings of the European conference on computer vision (2012)","DOI":"10.1007\/978-3-642-33765-9_50"},{"key":"1867_CR24","doi-asserted-by":"crossref","unstructured":"Wu, Y., Lim, J., and Yang, M.-H.: Online object tracking: A benchmark. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (2013)","DOI":"10.1109\/CVPR.2013.312"},{"key":"1867_CR25","doi-asserted-by":"crossref","unstructured":"Henriques, J.F., Caseiro, R., Martins, P., Batista, J.: High-speed tracking with kernelized correlation filters. In IEEE transactions on pattern analysis and machine intelligence (2015)","DOI":"10.1109\/TPAMI.2014.2345390"},{"key":"1867_CR26","unstructured":"Wang, N., Li, S., Gupta, A., Yeung, D.Y.: Transferring rich feature hierarchies for robust visual tracking (2015)"},{"key":"1867_CR27","doi-asserted-by":"crossref","unstructured":"Han, B., Sim, J., Adam, H.: Branch out: regularization for online ensemble tracking with convolutional neural networks. In: Conference on computer vision and pattern recognition pp. 521\u2013530 (2017)","DOI":"10.1109\/CVPR.2017.63"},{"issue":"2","key":"1867_CR28","first-page":"123","volume":"24","author":"L Breiman","year":"1996","unstructured":"Breiman, L.: Bagging predictors. Machine Learning. 24(2), 123\u2013140 (1996)","journal-title":"Machine Learning."},{"key":"1867_CR29","unstructured":"Ond\u0159ej, C., Ji\u0159\u00ed, M., Kittler J.: Locally optimized RANSAC. Lecture notes in computer science (2003)"},{"issue":"9","key":"1867_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TPAMI.2014.2388226","volume":"37","author":"Y Wu","year":"2015","unstructured":"Wu, Y., Lim, J., Yang, M.H.: Object tracking benchmark. IEEE Trans. Pattern Anal. Mach. Intell. 37(9), 1\u20131 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1867_CR31","doi-asserted-by":"crossref","unstructured":"J. F., Henriques, R., Caseiro, P., Martins, Batista, J.: High speed tracking with kernelized correlation filters. In IEEE transactions on pattern analysis and machine intelligence (2015)","DOI":"10.1109\/TPAMI.2014.2345390"},{"issue":"8","key":"1867_CR32","doi-asserted-by":"publisher","first-page":"1561","DOI":"10.1109\/TPAMI.2016.2609928","volume":"39","author":"M Danelljan","year":"2016","unstructured":"Danelljan, M., H\u00e4ger, G., Khan, F.S., et al.: Discriminative Scale Space Tracking. IEEE Trans. Pattern Anal. Mach. Intell. 39(8), 1561\u20131575 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1867_CR33","doi-asserted-by":"crossref","unstructured":"Danelljan, M., Bhat, G., Khan, F.S., and Felsberg, M.: Eco: Efficient convolution operators for tracking. In IEEE conference on computer vision and pattern recognition (2017)","DOI":"10.1109\/CVPR.2017.733"},{"key":"1867_CR34","unstructured":"Tony, L.: Scale invariant feature transform. Scholarpedia. (2012)"},{"key":"1867_CR35","doi-asserted-by":"crossref","unstructured":"Lucena, M. J., Fuertes, J. M., Gomez, J. I., et al.: Optical flow-based probabilistic tracking. (2003)","DOI":"10.1109\/ISSPA.2003.1224853"}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-021-01867-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-021-01867-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-021-01867-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,26]],"date-time":"2021-08-26T05:10:38Z","timestamp":1629954638000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-021-01867-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2,14]]},"references-count":35,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2021,10]]}},"alternative-id":["1867"],"URL":"https:\/\/doi.org\/10.1007\/s11760-021-01867-9","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"value":"1863-1703","type":"print"},{"value":"1863-1711","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,2,14]]},"assertion":[{"value":"28 November 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 November 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 January 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 February 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}