{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T15:31:33Z","timestamp":1761060693277},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030038007"},{"type":"electronic","value":"9783030038014"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"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":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-03801-4_42","type":"book-chapter","created":{"date-parts":[[2018,11,9]],"date-time":"2018-11-09T07:40:49Z","timestamp":1541749249000},"page":"474-486","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Convolutional Adaptive Particle Filter with Multiple Models for Visual Tracking"],"prefix":"10.1007","author":[{"given":"Reza Jalil","family":"Mozhdehi","sequence":"first","affiliation":[]},{"given":"Yevgeniy","family":"Reznichenko","sequence":"additional","affiliation":[]},{"given":"Abubakar","family":"Siddique","sequence":"additional","affiliation":[]},{"given":"Henry","family":"Medeiros","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,11,10]]},"reference":[{"key":"42_CR1","doi-asserted-by":"crossref","unstructured":"Choi, J., Chang, H.J., Jeong, J., Demiris, Y., Choi, J.Y.: Visual tracking using attention-modulated disintegration and integration. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2016","DOI":"10.1109\/CVPR.2016.468"},{"key":"42_CR2","doi-asserted-by":"crossref","unstructured":"Tang, M., Feng, J.: Multi-kernel correlation filter for visual tracking. In: IEEE International Conference on Computer Vision (ICCV), pp. 3038\u20133046 (2015)","DOI":"10.1109\/ICCV.2015.348"},{"key":"42_CR3","doi-asserted-by":"crossref","unstructured":"Danelljan, M., Hager, G., Khan, F.S., Felsberg, M.: Learning spatially regularized correlation filters for visual tracking. In: IEEE International Conference on Computer Vision (ICCV), December 2015","DOI":"10.1109\/ICCV.2015.490"},{"key":"42_CR4","doi-asserted-by":"crossref","unstructured":"Danelljan, M., Hager, G., Shahbaz Khan, F., Felsberg, M.: Convolutional features for correlation filter based visual tracking. In: IEEE International Conference on Computer Vision (ICCV) Workshops, December 2015","DOI":"10.1109\/ICCVW.2015.84"},{"key":"42_CR5","doi-asserted-by":"crossref","unstructured":"Ma, C., Huang, J.-B., Yang, X., Yang, M.-H.: Hierarchical convolutional features for visual tracking. In: IEEE International Conference on Computer Vision (ICCV), December 2015","DOI":"10.1109\/ICCV.2015.352"},{"issue":"3","key":"42_CR6","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1109\/TPAMI.2014.2345390","volume":"37","author":"JF Henriques","year":"2015","unstructured":"Henriques, J.F., Caseiro, R., Martins, P., Batista, J.: High-speed tracking with kernelized correlation filters. IEEE Trans. Pattern Anal. Mach. Intell. 37(3), 583\u2013596 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"42_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1007\/978-3-319-10599-4_13","volume-title":"Computer Vision","author":"J Zhang","year":"2014","unstructured":"Zhang, J., Ma, S., Sclaroff, S.: MEEM: robust tracking via multiple experts using entropy minimization. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8694, pp. 188\u2013203. Springer, Cham (2014). \nhttps:\/\/doi.org\/10.1007\/978-3-319-10599-4_13"},{"key":"42_CR8","doi-asserted-by":"crossref","unstructured":"Hare, S., Saffari, A., Torr, P.H.S.: Struck: structured output tracking with kernels. In: IEEE International Conference on Computer Vision (ICCV), pp. 263\u2013270. IEEE Computer Society (2011)","DOI":"10.1109\/ICCV.2011.6126251"},{"issue":"5","key":"42_CR9","doi-asserted-by":"publisher","first-page":"2356","DOI":"10.1109\/TIP.2014.2313227","volume":"23","author":"W Zhong","year":"2014","unstructured":"Zhong, W., Lu, H., Yang, M.H.: Robust object tracking via sparse collaborative appearance model. IEEE Trans. Image Process. 23(5), 2356\u20132368 (2014)","journal-title":"IEEE Trans. Image Process."},{"issue":"7","key":"42_CR10","doi-asserted-by":"publisher","first-page":"1409","DOI":"10.1109\/TPAMI.2011.239","volume":"34","author":"Z Kalal","year":"2012","unstructured":"Kalal, Z., Mikolajczyk, K., Matas, J.: Tracking-learning-detection. IEEE Trans. Pattern Anal. Mach. Intell. 34(7), 1409\u20131422 (2012)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"42_CR11","doi-asserted-by":"crossref","unstructured":"Mozhdehi, R.J., Reznichenko, Y., Siddique, A., Medeiros, H.: Deep convolutional particle filter with adaptive correlation maps for visual tracking. In: IEEE International Conference on Image Processing (ICIP) (2018)","DOI":"10.1109\/ICIP.2018.8451069"},{"key":"42_CR12","doi-asserted-by":"crossref","unstructured":"Mozhdehi, R.J., Medeiros, H.: Deep convolutional particle filter for visual tracking. In: IEEE International Conference on Image Processing (ICIP) (2017)","DOI":"10.1109\/ICIP.2017.8296963"},{"issue":"9","key":"42_CR13","doi-asserted-by":"publisher","first-page":"1844","DOI":"10.1016\/j.sigpro.2009.03.034","volume":"89","author":"HY Cheng","year":"2009","unstructured":"Cheng, H.Y., Hwang, J.N.: Adaptive particle sampling and adaptive appearance for multiple video object tracking. Signal Process. 89(9), 1844\u20131849 (2009)","journal-title":"Signal Process."},{"key":"42_CR14","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) (2013)","DOI":"10.1109\/CVPR.2013.312"},{"key":"42_CR15","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. In: International Conference on Learning Representations (ICLR) (2015)"},{"key":"42_CR16","doi-asserted-by":"crossref","unstructured":"Tao, R., Gavves, E., Smeulders, A.W.M.: Siamese instance search for tracking. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)","DOI":"10.1109\/CVPR.2016.158"},{"key":"42_CR17","doi-asserted-by":"crossref","unstructured":"Valmadre, J., Bertinetto, L., Henriques, J., Vedaldi, A., Torr, P.H.S.: End-to-end representation learning for correlation filter based tracking. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017","DOI":"10.1109\/CVPR.2017.531"},{"key":"42_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"850","DOI":"10.1007\/978-3-319-48881-3_56","volume-title":"Computer Vision \u2013 ECCV 2016 Workshops","author":"L Bertinetto","year":"2016","unstructured":"Bertinetto, L., Valmadre, J., Henriques, J.F., Vedaldi, A., Torr, P.H.S.: Fully-convolutional siamese networks for object tracking. In: Hua, G., J\u00e9gou, H. (eds.) ECCV 2016. LNCS, vol. 9914, pp. 850\u2013865. Springer, Cham (2016). \nhttps:\/\/doi.org\/10.1007\/978-3-319-48881-3_56"},{"key":"42_CR19","doi-asserted-by":"crossref","unstructured":"Ma, C., Yang, X., Zhang, C., Yang, M.-H.: Long-term correlation tracking. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5388\u20135396 (2015)","DOI":"10.1109\/CVPR.2015.7299177"},{"key":"42_CR20","unstructured":"Hong, S., You, T., Kwak, S., Han, B.: Online tracking by learning discriminative saliency map with convolutional neural network. In: 32nd International Conference on Machine Learning (2015)"}],"container-title":["Lecture Notes in Computer Science","Advances in Visual Computing"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-03801-4_42","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,11,9]],"date-time":"2018-11-09T07:58:25Z","timestamp":1541750305000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-03801-4_42"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030038007","9783030038014"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-03801-4_42","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"ISVC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Visual Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Las Vegas, NV","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","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":"19 November 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 November 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"isvc2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.isvc.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"113","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"66","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"58% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"2","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"54 papers were accepted for the main symposium out of 91 submissions; and 12 papers were accepted for the special tracks out of 22 submissions","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}