{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,22]],"date-time":"2025-05-22T04:15:08Z","timestamp":1747887308950,"version":"3.41.0"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2015,3,26]],"date-time":"2015-03-26T00:00:00Z","timestamp":1427328000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimedia Systems"],"published-print":{"date-parts":[[2016,6]]},"DOI":"10.1007\/s00530-015-0459-4","type":"journal-article","created":{"date-parts":[[2015,3,25]],"date-time":"2015-03-25T07:24:52Z","timestamp":1427268292000},"page":"297-313","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Robust visual tracking via online semi-supervised co-boosting"],"prefix":"10.1007","volume":"22","author":[{"given":"Si","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shunzhi","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Yan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2015,3,26]]},"reference":[{"issue":"4","key":"459_CR1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1177352.1177355","volume":"38","author":"A Yilmaz","year":"2006","unstructured":"Yilmaz, A., Javed, O., Shah, M.: Object tracking: a survey. ACM Comput. Surv. (CSUR) 38(4), 1\u201345 (2006)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"459_CR2","doi-asserted-by":"crossref","first-page":"3823","DOI":"10.1016\/j.neucom.2011.07.024","volume":"74","author":"H Yang","year":"2011","unstructured":"Yang, H., Shao, L., Zheng, F., Wang, L., Song, Z.: Recent advances and trends in visual tracking: a review. Neurocomputing 74, 3823\u20133831 (2011)","journal-title":"Neurocomputing"},{"issue":"6","key":"459_CR3","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1007\/s00530-012-0263-3","volume":"18","author":"N Ejaz","year":"2012","unstructured":"Ejaz, N., Baik, S.W.: Video summarization using a network of radial basis functions. Multimedia Syst. 18(6), 483\u2013497 (2012)","journal-title":"Multimedia Syst."},{"issue":"1","key":"459_CR4","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1007\/s11263-012-0564-1","volume":"101","author":"C Vondrick","year":"2013","unstructured":"Vondrick, C., Patterson, D., Ramanan, D.: Efficiently scaling up crowdsourced video annotation. Int. J. Comput. Vis. 101(1), 184\u2013204 (2013)","journal-title":"Int. J. Comput. Vis."},{"key":"459_CR5","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Huang, K., Tan, T., Wang, Y.: 3D model based vehicle tracking using gradient based fitness evaluation under particle filter framework. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1771\u20131774 (2010)","DOI":"10.1109\/ICPR.2010.437"},{"issue":"11","key":"459_CR6","doi-asserted-by":"crossref","first-page":"1115","DOI":"10.1109\/34.544082","volume":"18","author":"WF Gardner","year":"1996","unstructured":"Gardner, W.F., Lawton, D.T.: Interactive model-based vehicle tracking. IEEE Trans. Pattern Anal. Mach. Intell. 18(11), 1115\u20131121 (1996)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"1","key":"459_CR7","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1007\/s11263-007-0075-7","volume":"77","author":"DA Ross","year":"2008","unstructured":"Ross, D.A., Lim, J., Lin, R.S., Yang, M.H.: Incremental learning for robust visual tracking. Int. J. Comput. Vis. 77(1), 125\u2013141 (2008)","journal-title":"Int. J. Comput. Vis."},{"key":"459_CR8","author":"T Ren","year":"2014","unstructured":"Ren, T., Qiu, Z., Liu, Y., Yu, T., Bei, J.: Soft-assigned bag of features for object tracking. Multimedia Syst. (2014). doi: 10.1007\/s00530-014-0384-y","journal-title":"Multimedia Syst."},{"issue":"5","key":"459_CR9","doi-asserted-by":"crossref","first-page":"1238","DOI":"10.1109\/TRO.2008.2003281","volume":"24","author":"Y Yoon","year":"2008","unstructured":"Yoon, Y., Kosaka, A., Kak, A.C.: A new Kalman-filter-based framework for fast and accurate visual tracking of rigid objects. IEEE Trans. Robot. 24(5), 1238\u20131251 (2008)","journal-title":"IEEE Trans. Robot."},{"key":"459_CR10","doi-asserted-by":"crossref","unstructured":"Bao, C., Wu, Y., Ling, H., Ji, H.: Real time robust L1 tracker using accelerated proximal gradient approach. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1830\u20131837 (2012)","DOI":"10.1109\/CVPR.2012.6247881"},{"issue":"8","key":"459_CR11","doi-asserted-by":"crossref","first-page":"1064","DOI":"10.1109\/TPAMI.2004.53","volume":"26","author":"S Avidan","year":"2004","unstructured":"Avidan, S.: Support vector tracking. IEEE Trans. Pattern Anal. Mach. Intell. 26(8), 1064\u20131072 (2004)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"459_CR12","doi-asserted-by":"crossref","unstructured":"Avidan, S.: Ensemble tracking. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 494\u2013501 (2005)","DOI":"10.1109\/CVPR.2005.144"},{"key":"459_CR13","doi-asserted-by":"crossref","unstructured":"Grabner, H., Bischof, H.: On-line boosting and vision. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 260\u2013267 (2006)","DOI":"10.1109\/CVPR.2006.215"},{"key":"459_CR14","doi-asserted-by":"crossref","unstructured":"Grabner, H., Grabner, M., Bischof, H.: Real-time tracking via on-line boosting. In: British Machine Vision Conference (BMVC), pp. 47\u201356 (2006)","DOI":"10.5244\/C.20.6"},{"key":"459_CR15","unstructured":"Oza, N., Russell, S.: Online bagging and boosting. In: International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 105\u2013112 (2001)"},{"key":"459_CR16","doi-asserted-by":"crossref","unstructured":"Hare, S., Saffari, A., Torr, P.H.: Struck: structured output tracking with kernels. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 263\u2013270 (2011)","DOI":"10.1109\/ICCV.2011.6126251"},{"issue":"8","key":"459_CR17","doi-asserted-by":"crossref","first-page":"1619","DOI":"10.1109\/TPAMI.2010.226","volume":"33","author":"B Babenko","year":"2011","unstructured":"Babenko, B., Yang, M.H., Belongie, S.: Robust object tracking with online multiple instance learning. IEEE Trans. Pattern Anal. Mach. Intell. 33(8), 1619\u20131632 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"1","key":"459_CR18","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1016\/j.patcog.2012.07.013","volume":"46","author":"K Zhang","year":"2013","unstructured":"Zhang, K., Song, H.: Real-time visual tracking via online weighted multiple instance learning. Pattern Recognit. 46(1), 397\u2013411 (2013)","journal-title":"Pattern Recognit."},{"key":"459_CR19","doi-asserted-by":"crossref","unstructured":"Zhang, K., Zhang, L., Yang, M.H.: Real-time compressive tracking. In: European Conference on Computer Vision (ECCV), pp. 866\u2013879 (2012)","DOI":"10.1007\/978-3-642-33712-3_62"},{"key":"459_CR20","doi-asserted-by":"crossref","unstructured":"Grabner, H., Leistner, C., Bischof, H.: Semi-supervised on-line boosting for robust tracking. In: European Conference on Computer Vision (ECCV), pp. 234\u2013247 (2008)","DOI":"10.1007\/978-3-540-88682-2_19"},{"key":"459_CR21","doi-asserted-by":"crossref","unstructured":"Tang, F., Brennan, S., Zhao, Q., Tao, H.: Co-tracking using semi-supervised support vector machines. In: IEEE International Conference on Computer Vision (ICCV), pp. 1\u20138 (2007)","DOI":"10.1109\/ICCV.2007.4408954"},{"key":"459_CR22","doi-asserted-by":"crossref","unstructured":"Liu, R., Cheng, J., Lu, H.: A robust boosting tracker with minimum error bound in a co-training framework. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1459\u20131466 (2009)","DOI":"10.1109\/ICCV.2009.5459285"},{"key":"459_CR23","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1016\/j.patrec.2011.11.019","volume":"33","author":"MC Ho","year":"2012","unstructured":"Ho, M.C., Chiang, C.C., Su, Y.Y.: Object tracking by exploiting adaptive region-wise linear subspace representations and adaptive templates in an iterative particle filter. Pattern Recognit. Lett. 33, 500\u2013512 (2012)","journal-title":"Pattern Recognit. Lett."},{"issue":"2","key":"459_CR24","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1007\/s00530-004-0147-2","volume":"10","author":"L Jiao","year":"2004","unstructured":"Jiao, L., Wu, Y., Wu, G., Chang, E.Y., Wang, Y.: Anatomy of a multicamera video surveillance system. Multimedia Syst. 10(2), 144\u2013163 (2004)","journal-title":"Multimedia Syst."},{"key":"459_CR25","doi-asserted-by":"crossref","unstructured":"Leistner, C., Saffari, A., Roth, P., Bischof, H.: On robustness of on-line boosting\u2014a competitive study. In: IEEE International Conference on Computer Vision (ICCV), pp. 1362\u20131369 (2009)","DOI":"10.1109\/ICCVW.2009.5457451"},{"key":"459_CR26","doi-asserted-by":"crossref","unstructured":"Kalal, Z., Matas, J., Mikolajczyk, K.: P-N learning: bootstrapping binary classifiers by structural constraints. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 49\u201356 (2010)","DOI":"10.1109\/CVPR.2010.5540231"},{"key":"459_CR27","doi-asserted-by":"crossref","unstructured":"Zhang, K., Zhang, L., Yang, M.H.: Real-time compressive tracking, In: European Conference on Computer Vision (ECCV), pp. 866\u2013879 (2012)","DOI":"10.1007\/978-3-642-33712-3_62"},{"key":"459_CR28","doi-asserted-by":"crossref","unstructured":"Rosenberg, C., Hebert, M., Schneiderman, H.: Semi-supervised self-training of object detection models. In: IEEE Workshop on Applications of Computer Vision (WACV), pp. 29\u201336 (2005)","DOI":"10.1109\/ACVMOT.2005.107"},{"key":"459_CR29","unstructured":"Zhu, X.: Semi-supervised learning literature survey. In: Computer Sciences TR-1530. University of Wisconsin-Madison, USA (2007)"},{"key":"459_CR30","doi-asserted-by":"crossref","unstructured":"Blum, A., Mitchell, T.: Combining labeled and unlabeled data with co-training. In: Annual Conference on Computational Learning Theory (COLT), pp. 92\u2013100 (1998)","DOI":"10.1145\/279943.279962"},{"key":"459_CR31","doi-asserted-by":"crossref","unstructured":"Nigam, K., Ghani R.: Analyzing the effectiveness and applicability of co-training. In: ACM International Conference on Information and Knowledge Management (CIKM), pp. 86\u201393 (2000)","DOI":"10.1145\/354756.354805"},{"key":"459_CR32","unstructured":"Balcan, M.F., Blum, A., Yang, K.: Co-training and expansion: Towards bridging theory and practice. In: Advances in Neural Information Processing Systems (NIPS), pp. 89\u201396 (2005)"},{"issue":"9","key":"459_CR33","doi-asserted-by":"crossref","first-page":"1203","DOI":"10.1109\/TCSVT.2011.2130270","volume":"21","author":"C Liu","year":"2011","unstructured":"Liu, C., Yuen, P.C.: A boosted co-training algorithm for human action recognition. IEEE Trans. Circ. Syst. Vid. 21(9), 1203\u20131213 (2011)","journal-title":"IEEE Trans. Circ. Syst. Vid."},{"issue":"11","key":"459_CR34","doi-asserted-by":"crossref","first-page":"2000","DOI":"10.1109\/TPAMI.2008.235","volume":"31","author":"PK Mallapragada","year":"2009","unstructured":"Mallapragada, P.K., Rong, J., Jain, A.K., Yi, L.: SemiBoost: boosting for semi-supervised learning. IEEE Trans. Pattern Anal. Mach. Intell. 31(11), 2000\u20132014 (2009)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"459_CR35","doi-asserted-by":"crossref","unstructured":"Leistner, C., Grabner, H., Bischof, H.: Semi-supervised boosting using visual similarity learning. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1\u20138 (2008)","DOI":"10.1109\/CVPR.2008.4587629"},{"issue":"6","key":"459_CR36","doi-asserted-by":"crossref","first-page":"1677","DOI":"10.1109\/TMM.2014.2323014","volume":"16","author":"Y Yang","year":"2014","unstructured":"Yang, Y., Zha, Z., Gao, Y.: Xiaofeng Zhu, Tat-Seng Chua, Exploiting web images for semantic video indexing via robust sample-specific loss. IEEE Trans. Multimedia 16(6), 1677\u20131689 (2014)","journal-title":"IEEE Trans. Multimedia"},{"issue":"2","key":"459_CR37","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1145\/2457450.2457456","volume":"9","author":"Y Yang","year":"2013","unstructured":"Yang, Y., Yang, Y., Shen, H.: Effective transfer tagging from image to video. ACM Trans. Multimedia Comput. Commun. Appl. 9(2), 14 (2013)","journal-title":"ACM Trans. Multimedia Comput. Commun. Appl."},{"issue":"10","key":"459_CR38","doi-asserted-by":"crossref","first-page":"1345","DOI":"10.1109\/TKDE.2009.191","volume":"22","author":"S Pan","year":"2010","unstructured":"Pan, S., Yang, Q.: A survey on transfer learning. IEEE Trans. Knowl. Data Eng. 22(10), 1345\u20131359 (2010)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"459_CR39","unstructured":"Schapire, R.E., Rochery, M., Rahim, M., Gupta, N.: Incorporating prior knowledge into boosting. In: International Conference on Machine Learning (ICML), pp. 538\u2013545 (2002)"},{"key":"459_CR40","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1016\/j.neucom.2014.02.031","volume":"139","author":"S Chen","year":"2014","unstructured":"Chen, S., Li, S., Su, S., Tian, Q., Ji, R.: Online MIL tracking with instance-level semi-supervised learning. Neurocomputing 139, 272\u2013288 (2014)","journal-title":"Neurocomputing"},{"issue":"2","key":"459_CR41","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1214\/aos\/1016218223","volume":"28","author":"J Friedman","year":"2000","unstructured":"Friedman, J., Hastie, T., Tibshirani, R.: Additive logistic regression: a statistical view of boosting. Ann. Stat. 28(2), 337\u2013407 (2000)","journal-title":"Ann. Stat."},{"key":"459_CR42","unstructured":"Oza, N.: Online ensemble learning. Ph.D. thesis. University of California, Berkeley (2001)"},{"key":"459_CR43","doi-asserted-by":"crossref","unstructured":"Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: IEEE International Conference on Computer Vision (ICCV), pp. 511\u2013518 (2001)","DOI":"10.1109\/CVPR.2001.990517"},{"issue":"12","key":"459_CR44","doi-asserted-by":"crossref","first-page":"2037","DOI":"10.1109\/TPAMI.2006.244","volume":"28","author":"T Ahonen","year":"2006","unstructured":"Ahonen, T., Hadid, A., Pietikainen, M.: Face description with local binary patterns: application to face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 28(12), 2037\u20132041 (2006)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"459_CR45","unstructured":"Welch, G., Bishop, G.: An introduction to the Kalman filter. Technical report. UNC-CH Computer Science Technical Report 95041 (1995)"},{"key":"459_CR46","doi-asserted-by":"crossref","unstructured":"Wu, Y., Lim, J., Yang, M.H.: Online object tracking: a benchmark, In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2411\u20132418 (2013)","DOI":"10.1109\/CVPR.2013.312"},{"key":"459_CR47","unstructured":"Everingham, M., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman A.: The PASCAL visual object classes challenge 2010 (VOC2010) results (2010)"},{"key":"459_CR48","author":"L Ying","year":"2014","unstructured":"Ying, L., Zhang, T., Xu, C.: Multi-object tracking via MHT with multiple information fusion in surveillance video. Multimedia Syst. (2014). doi: 10.1007\/s00530-014-0361-5","journal-title":"Multimedia Syst."}],"container-title":["Multimedia Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-015-0459-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00530-015-0459-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-015-0459-4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,21]],"date-time":"2025-05-21T15:54:23Z","timestamp":1747842863000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00530-015-0459-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,3,26]]},"references-count":48,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2016,6]]}},"alternative-id":["459"],"URL":"https:\/\/doi.org\/10.1007\/s00530-015-0459-4","relation":{},"ISSN":["0942-4962","1432-1882"],"issn-type":[{"type":"print","value":"0942-4962"},{"type":"electronic","value":"1432-1882"}],"subject":[],"published":{"date-parts":[[2015,3,26]]}}}