{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,4]],"date-time":"2025-05-04T05:10:01Z","timestamp":1746335401770,"version":"3.40.4"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2014,8,13]],"date-time":"2014-08-13T00:00:00Z","timestamp":1407888000000},"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":["Vis Comput"],"published-print":{"date-parts":[[2015,10]]},"DOI":"10.1007\/s00371-014-1012-8","type":"journal-article","created":{"date-parts":[[2014,8,12]],"date-time":"2014-08-12T17:28:20Z","timestamp":1407864500000},"page":"1307-1318","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Robust object tracking with active context learning"],"prefix":"10.1007","volume":"31","author":[{"given":"Wei","family":"Quan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongquan","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianjun","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jim X.","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2014,8,13]]},"reference":[{"key":"1012_CR1","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1008078328650","volume":"29","author":"M Isard","year":"1998","unstructured":"Isard, M., Blake, A.: CONDENSATION\u2014Conditional density propagation for visual tracking. Int\u2019l J. Comput. Vis. (IJCV) 29, 5\u201328 (1998)","journal-title":"Int\u2019l J. Comput. Vis. (IJCV)"},{"issue":"5","key":"1012_CR2","doi-asserted-by":"crossref","first-page":"564","DOI":"10.1109\/TPAMI.2003.1195991","volume":"25","author":"D Comaniciu","year":"2003","unstructured":"Comaniciu, D., Ramesh, V., Meer, P.: Kernel-based object tracking. IEEE Trans. Pattern Anal. Mach. Intell. 25(5), 564\u2013577 (May 2003)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"4","key":"1012_CR3","doi-asserted-by":"crossref","first-page":"13","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. 38(4), 13 (Dec. 2006)","journal-title":"ACM Comput. Surv."},{"issue":"2","key":"1012_CR4","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1109\/TPAMI.2007.35","volume":"29","author":"S Avidan","year":"2007","unstructured":"Avidan, S.: Ensemble tracking. IEEE Trans. Pattern Anal. Mach. Intell. 29(2), 261\u2013271 (2007)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"10","key":"1012_CR5","doi-asserted-by":"crossref","first-page":"1631","DOI":"10.1109\/TPAMI.2005.205","volume":"27","author":"R Collins","year":"2005","unstructured":"Collins, R., Liu, Y., Leordeanu, M.: Online selection of discriminative tracking features. IEEE Trans. Pattern Anal. Mach. Intell. 27(10), 1631\u20131643 (2005)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1012_CR6","unstructured":"Lim, J., Ross, D., Lin, R., Yang, M.: Incremental learning for visual tracking. Neural Inf. Process. Systems (NIPS) (2005)"},{"key":"1012_CR7","first-page":"260","volume":"1","author":"H Grabner","year":"2006","unstructured":"Grabner, H., Bischof, H.: On-line boosting and vision. IEEE Conf. Comput. Vis. Pattern Recogn. (CVPR) 1, 260\u2013267 (2006)","journal-title":"IEEE Conf. Comput. Vis. Pattern Recogn. (CVPR)"},{"key":"1012_CR8","doi-asserted-by":"crossref","unstructured":"Saffari, A., Leistner, C., Santner, J., Godec, M., Bischof, H.: On-line random forests. IEEE Int\u2019l Conf, Computer Vision (ICCV), WS on On-line Learning for Computer Vision (2009)","DOI":"10.1109\/ICCVW.2009.5457447"},{"key":"1012_CR9","doi-asserted-by":"crossref","unstructured":"Wang, A., Wan, G., Cheng, Z., Li, S.: An incremental extremely random forest classifier for online learning and tracking. IEEE Int\u2019l Conf. Image Processing (ICIP), pp. 1449\u20131452 (2009)","DOI":"10.1109\/ICIP.2009.5414559"},{"key":"1012_CR10","doi-asserted-by":"crossref","unstructured":"Grabner, H., Leistner, C., Bischof, H.: Semi-supervised on-line boosting for robust tracking. European Conference on Computer Vision (ECCV) (2008)","DOI":"10.1007\/978-3-540-88682-2_19"},{"key":"1012_CR11","doi-asserted-by":"crossref","unstructured":"Stalder, S., Grabner, H., van Gool, L., Zurich, E., Leuven, K.: Beyond semi-supervised tracking: tracking should be as simple as detection, but not simpler than recognition. IEEE Int\u2019l Conf, Computer Vision (ICCV), WS on On-line Learning for Computer Vision (2009)","DOI":"10.1109\/ICCVW.2009.5457445"},{"key":"1012_CR12","doi-asserted-by":"crossref","unstructured":"Leistner, C., Saffari, A., Santner, J., Bischof, H.: Semi-supervised random forests. IEEE Int\u2019l Conf, Computer Vision (ICCV) (2009)","DOI":"10.1109\/ICCV.2009.5459198"},{"key":"1012_CR13","doi-asserted-by":"crossref","unstructured":"Leistner, C., Godec, M., Saffari, A., Bischof, H.: On-line multi-view forests for tracking. DAGM-Symposium, pp. 493\u2013502 (2010)","DOI":"10.1007\/978-3-642-15986-2_50"},{"volume-title":"Semi-Supervised Learning","year":"2006","key":"1012_CR14","unstructured":"Chapelle, O., Scholkopf, B., Zien, A. (eds.): Semi-Supervised Learning. MIT Press, Cambridge, MA (2006)"},{"key":"1012_CR15","doi-asserted-by":"crossref","unstructured":"Babenko, B., Yang, M.-H., Belongie, S.: Visual tracking with online multiple instance learning. IEEE Conf, Computer Vision and Pattern Recognition (CVPR) (2009)","DOI":"10.1109\/CVPRW.2009.5206737"},{"key":"1012_CR16","doi-asserted-by":"crossref","unstructured":"Leistner, C., Saffari, A., Bischof, H.: MILForests: multiple-instance learning with randomized trees. European Conference on Computer Vision (ECCV) (2010).","DOI":"10.1007\/978-3-642-15567-3_3"},{"key":"1012_CR17","doi-asserted-by":"crossref","unstructured":"Yu, Q., Dinh, T., Medioni, G.: Online tracking and reacquisition using co-trained generative and discriminative trackers. European Conference on Computer Vision (ECCV) (2008)","DOI":"10.1007\/978-3-540-88688-4_50"},{"key":"1012_CR18","doi-asserted-by":"crossref","unstructured":"Kalal, Z., Matas, J., Mikolajczyk, K.: Online learning of robust object detectors during unstable tracking. IEEE Int\u2019l Conf, Computer Vision (ICCV), WS on On-line Learning for Computer Vision (2009)","DOI":"10.1109\/ICCVW.2009.5457446"},{"key":"1012_CR19","doi-asserted-by":"crossref","unstructured":"Kalal, Z., Matas, J., Mikolajczyk, K.: P-N learning: bootstrapping binary classifiers by structural constraints. IEEE Conf, Computer Vision and Pattern Recognition (CVPR) (2010)","DOI":"10.1109\/CVPR.2010.5540231"},{"key":"1012_CR20","doi-asserted-by":"crossref","unstructured":"Zhong, W., Lu, H., Yang, M.: Robust object tracking via sparsity-based collaborative model. IEEE Conf, Computer Vision and Pattern Recognition (CVPR) (2012)","DOI":"10.1109\/CVPR.2012.6247882"},{"key":"1012_CR21","doi-asserted-by":"crossref","first-page":"1195","DOI":"10.1109\/TPAMI.2008.146","volume":"31","author":"M Yang","year":"2009","unstructured":"Yang, M., Wu, Y., Hua, G.: Context-aware visual tracking. IEEE Trans. Pattern Anal. Mach. Intell. 31, 1195\u20131209 (2009)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1012_CR22","doi-asserted-by":"crossref","unstructured":"Grabner, H., Matas, J., Gool, L.V., Cattin, P.: Tracking the invisible: learning where the object might be. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), pp. 1285\u20131292 (2010).","DOI":"10.1109\/CVPR.2010.5539819"},{"key":"1012_CR23","doi-asserted-by":"crossref","unstructured":"Dinh, T.B., Vo, N., Medioni, G.: Context tracker: exploring supporters and distracters in unconstrained environments. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), pp. 1177\u20131184 (2011).","DOI":"10.1109\/CVPR.2011.5995733"},{"key":"1012_CR24","doi-asserted-by":"crossref","unstructured":"Fan, J., Wu, Y., Dai, S.: Discriminative spatial attention for robust tracking. European Conference on Computer Vision (ECCV), pp. 480\u2013493 (2010).","DOI":"10.1007\/978-3-642-15549-9_35"},{"key":"1012_CR25","doi-asserted-by":"crossref","unstructured":"Godec, M., Sternig, S., Roth, P.M., Bischof, H.: Context-driven clustering by multi-class classification in an active learning framework. IEEE Conf. Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 19\u201324 (2010).","DOI":"10.1109\/CVPRW.2010.5543886"},{"key":"1012_CR26","unstructured":"Shakhnarovich, G., Darrell, T., Indyk, P.: Nearest-Neighbor Methods in Learning and Vision: Theory and Practice, MIT Press, Cambridge (2005)."},{"key":"1012_CR27","doi-asserted-by":"crossref","unstructured":"Stenger, B., Woodley, T., Cipolla, R.: Learning to track with multiple observers. IEEE Conf, Computer Vision and Pattern Recognition (CVPR), Miami (2009)","DOI":"10.1109\/CVPR.2009.5206634"},{"key":"1012_CR28","doi-asserted-by":"crossref","unstructured":"Ozuysal, M., Fua, P., Lepetit, V.: Fast keypoint recognition in ten lines of code. IEEE Conf, Computer Vision and Pattern Recognition (CVPR) (2007)","DOI":"10.1109\/CVPR.2007.383123"},{"key":"1012_CR29","doi-asserted-by":"crossref","unstructured":"Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. IEEE Conf, Computer Vision and Pattern Recognition (CVPR) (2001)","DOI":"10.1109\/CVPR.2001.990517"},{"key":"1012_CR30","doi-asserted-by":"crossref","unstructured":"Agarwal, S., Awan, A., Roth, D.: Learning to detect objects in images via a sparse, part-based representation. IEEE Trans. Pattern Anal. Mach. Intell (2004).","DOI":"10.1109\/TPAMI.2004.108"},{"key":"1012_CR31","doi-asserted-by":"crossref","unstructured":"Adam, A., Rivlin, E., Shimshoni, I.: Robust fragments-based tracking using the integral histogram. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), pp. 798\u2013805 (2006)","DOI":"10.1109\/CVPR.2006.256"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-014-1012-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00371-014-1012-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-014-1012-8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,4]],"date-time":"2025-05-04T04:50:35Z","timestamp":1746334235000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00371-014-1012-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,8,13]]},"references-count":31,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2015,10]]}},"alternative-id":["1012"],"URL":"https:\/\/doi.org\/10.1007\/s00371-014-1012-8","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"type":"print","value":"0178-2789"},{"type":"electronic","value":"1432-2315"}],"subject":[],"published":{"date-parts":[[2014,8,13]]}}}