{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T07:28:44Z","timestamp":1780385324884,"version":"3.54.1"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2016,11,24]],"date-time":"2016-11-24T00:00:00Z","timestamp":1479945600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/K031910\/1"],"award-info":[{"award-number":["EP\/K031910\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Real-Time Image Proc"],"published-print":{"date-parts":[[2019,10]]},"DOI":"10.1007\/s11554-016-0654-3","type":"journal-article","created":{"date-parts":[[2016,11,24]],"date-time":"2016-11-24T11:05:04Z","timestamp":1479985504000},"page":"1439-1458","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":43,"title":["DS-KCF: a real-time tracker for RGB-D data"],"prefix":"10.1007","volume":"16","author":[{"given":"Sion","family":"Hannuna","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Massimo","family":"Camplani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jake","family":"Hall","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Majid","family":"Mirmehdi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dima","family":"Damen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tilo","family":"Burghardt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adeline","family":"Paiement","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lili","family":"Tao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2016,11,24]]},"reference":[{"issue":"8","key":"654_CR1","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. IEEE Trans. Pattern Anal. Mach. Intell. 26(8), 1064\u20131072 (2004)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"654_CR2","doi-asserted-by":"crossref","unstructured":"Awwad, S., Hussein, F., Piccardi, M.: Local depth patterns for tracking in depth videos. In: ACM Multimedia, pp. 1115\u20131118 (2015)","DOI":"10.1145\/2733373.2806295"},{"key":"654_CR3","doi-asserted-by":"crossref","unstructured":"Bolme, D., Beveridge, J., Draper, B., Lui, Y.M.: Visual object tracking using adaptive correlation filters. In: IEEE CVPR, pp. 2544\u20132550 (2010)","DOI":"10.1109\/CVPR.2010.5539960"},{"issue":"3","key":"654_CR4","doi-asserted-by":"publisher","first-page":"500","DOI":"10.1109\/TPAMI.2010.143","volume":"33","author":"T Brox","year":"2011","unstructured":"Brox, T., Malik, J.: Large displacement optical flow: descriptor matching in variational motion estimation. IEEE Trans. Pattern Anal. Mach. Intell. 33(3), 500\u2013513 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"6","key":"654_CR5","doi-asserted-by":"publisher","first-page":"1560","DOI":"10.1109\/TCYB.2013.2271112","volume":"43","author":"M Camplani","year":"2013","unstructured":"Camplani, M., Mantecon, T., Salgado, L.: Depth-color fusion strategy for 3-D scene modeling with kinect. IEEE Trans. Cybern. 43(6), 1560\u20131571 (2013)","journal-title":"IEEE Trans. Cybern."},{"key":"654_CR6","doi-asserted-by":"crossref","unstructured":"Camplani, M., Hannuna, S., Mirmehdi, M., Damen, D., Paiement, A., Tao, L., Burghardt, T.: Real-time RGB-D tracking with depth scaling kernelised correlation filters and occlusion handling. In: BMVC, pp. 145.1\u2013145.11 (2015)","DOI":"10.5244\/C.29.145"},{"key":"654_CR7","doi-asserted-by":"crossref","unstructured":"Camplani, M., Paiement, A., Mirmehdi, M., Damen, D., Hannuna, S., Tao, L., Burghardt, T.: Multiple human tracking from RGB-D data: a survey. IET Comput. Vis. (2017) (to appear)","DOI":"10.1049\/iet-cvi.2016.0178"},{"key":"654_CR8","doi-asserted-by":"crossref","unstructured":"Chen, T., Chen, Y., Chien, S.: Fast image segmentation based on K-means clustering with histograms in HSV colour space. In: IEEE MSP workshop, pp. 322\u2013325 (2008)","DOI":"10.1109\/MMSP.2008.4665097"},{"key":"654_CR9","unstructured":"Chen, Z., Hong, Z., Tao, D.: An experimental survey on correlation filter-based tracking. CoRR abs\/1509.05520, http:\/\/arxiv.org\/abs\/1509.05520 (2015)"},{"key":"654_CR10","first-page":"217","volume":"9386","author":"D Chrapek","year":"2015","unstructured":"Chrapek, D., Beran, V., Zemcik, P.: Depth-based filtration for tracking boost. ACIVS 9386, 217\u2013228 (2015)","journal-title":"ACIVS"},{"key":"654_CR11","doi-asserted-by":"crossref","unstructured":"Danelljan, M., H\u00e4ger, G., Shahbaz Khan, F., Felsberg, M.: Accurate scale estimation for robust visual tracking. In: BMVC, pp. 38.1\u201338.11 (2014a)","DOI":"10.5244\/C.28.65"},{"key":"654_CR12","doi-asserted-by":"crossref","unstructured":"Danelljan, M., Khan, F., Felsberg, M., van\u00a0de Weijer, J.: Adaptive color attributes for real-time visual tracking. In: IEEE CVPR, pp. 1090\u20131097 (2014b)","DOI":"10.1109\/CVPR.2014.143"},{"key":"654_CR13","doi-asserted-by":"crossref","unstructured":"Du, Q., Cai, Z.q., Liu, H., Yu, Z.L.: A rotation adaptive correlation filter for robust tracking. In: IEEE DSP, pp. 1035\u20131038 (2015)","DOI":"10.1109\/ICDSP.2015.7252035"},{"key":"654_CR14","doi-asserted-by":"crossref","unstructured":"Galoogahi, H., Sim, T., Lucey, S.: Multi-channel correlation filters. In: IEEE ICCV, pp. 3072\u20133079 (2013)","DOI":"10.1109\/ICCV.2013.381"},{"key":"654_CR15","first-page":"357","volume-title":"Lecture Notes in Computer Science","author":"Germ\u00e1n Mart\u00edn Garc\u00eda","year":"2012","unstructured":"Garc\u00eda, G., Klein, D., St\u00fcckler, J., Frintrop, S., Cremers, A.: Adaptive multi-cue 3D tracking of arbitrary objects. In: Pattern Recognition, pp. 357\u2013366 (2012)"},{"key":"654_CR16","volume-title":"Digital Image Processing","author":"R Gonzalez","year":"1992","unstructured":"Gonzalez, R., Woods, R.: Digital Image Processing. Addison-Wesley Longman Publishing Co. Inc, Reading (1992)"},{"key":"654_CR17","doi-asserted-by":"crossref","unstructured":"Gupta, S., Arbelaez, P., Malik, J.: Perceptual organization and recognition of indoor scenes from RGB-D images. In: IEEE CVPR, pp. 564\u2013571 (2013)","DOI":"10.1109\/CVPR.2013.79"},{"key":"654_CR18","first-page":"345","volume":"8695","author":"S Gupta","year":"2014","unstructured":"Gupta, S., Girshick, R., Arbel\u00e1ez, P., Malik, J.: Learning rich features from RGB-D images for object detection and segmentation. ECCV 8695, 345\u2013360 (2014)","journal-title":"ECCV"},{"key":"654_CR19","unstructured":"Haag, K.: KCF implementation C++. GitHub repository. https:\/\/github.com\/klahaag\/cf_tracking (2015)"},{"issue":"5","key":"654_CR20","doi-asserted-by":"publisher","first-page":"1318","DOI":"10.1109\/TCYB.2013.2265378","volume":"43","author":"J Han","year":"2013","unstructured":"Han, J., Shao, L., Xu, D., Shotton, J.: Enhanced computer vision with microsoft kinect sensor: a review. IEEE T-Cybern. 43(5), 1318\u20131334 (2013)","journal-title":"IEEE T-Cybern."},{"key":"654_CR21","doi-asserted-by":"crossref","unstructured":"Hare, S., Saffari, A., Torr, P.: Struck: structured output tracking with kernels. In: IEEE ICCV, pp. 263\u2013270 (2011)","DOI":"10.1109\/ICCV.2011.6126251"},{"issue":"3","key":"654_CR22","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":"654_CR23","doi-asserted-by":"publisher","first-page":"1758","DOI":"10.1364\/AO.19.001758","volume":"19","author":"CF Hester","year":"1980","unstructured":"Hester, C.F., Casasent, D.: Multivariant technique for multiclass pattern recognition. Appl. Opt. 19, 1758\u20131761 (1980)","journal-title":"Appl. Opt."},{"issue":"7","key":"654_CR24","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."},{"issue":"2","key":"654_CR25","doi-asserted-by":"publisher","first-page":"1437","DOI":"10.3390\/s120201437","volume":"12","author":"K Khoshelham","year":"2012","unstructured":"Khoshelham, K., Elberink, S.: Accuracy and resolution of kinect depth data for indoor mapping applications. Sensors 12(2), 1437\u20131454 (2012)","journal-title":"Sensors"},{"key":"654_CR26","doi-asserted-by":"crossref","unstructured":"Klein, D., Cremers, A.: Boosting scalable gradient features for adaptive real-time tracking. In: IEEE ICRA, pp. 4411\u20134416 (2011)","DOI":"10.1109\/ICRA.2011.5980369"},{"key":"654_CR27","unstructured":"Kristan, M., et\u00a0al.: The Visual Object Tracking VOT2014 challenge results. In: ECCV Visual Object Tracking Challenge Workshop (2014)"},{"key":"654_CR28","doi-asserted-by":"crossref","unstructured":"Kwon, J., Lee, K.: Visual tracking decomposition. In: IEEE CVPR, pp. 1269\u20131276 (2010)","DOI":"10.1109\/CVPR.2010.5539821"},{"key":"654_CR29","unstructured":"Leal-Taix\u00e9, L., Milan, A., Reid, I., Roth, S., Schindler, K.: MOTChallenge 2015: towards a benchmark for multi-target tracking. arXiv:150401942 [cs] (2015)"},{"issue":"4","key":"654_CR30","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1145\/2508037.2508039","volume":"4","author":"X Li","year":"2013","unstructured":"Li, X., Hu, W., Shen, C., Zhang, Z., Dick, A., Hengel, A.: A survey of appearance models in visual object tracking. ACM Trans. Intell. Syst. Technol. 4(4), 271\u2013288 (2013)","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"654_CR31","doi-asserted-by":"crossref","unstructured":"Li, Y., Zhu, J.: A scale adaptive Kernel correlation filter tracker with feature integration. ECCV Workshops, vol. 8926, pp. 254\u2013265 (2015)","DOI":"10.1007\/978-3-319-16181-5_18"},{"key":"654_CR32","doi-asserted-by":"crossref","unstructured":"Li, Y., Zhu, J., Hoi, S.C.: Reliable patch trackers: Robust visual tracking by exploiting reliable patches. In: IEEE CVPR, pp. 353\u2013361 (2015)","DOI":"10.1109\/CVPR.2015.7298632"},{"key":"654_CR33","doi-asserted-by":"crossref","unstructured":"Liu, T., Wang, G., Yang, Q.: Real-time part-based visual tracking via adaptive correlation filters. In: IEEE CVPR, pp. 4902\u20134912 (2015)","DOI":"10.1109\/CVPR.2015.7299124"},{"issue":"2","key":"654_CR34","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1109\/TIT.1982.1056489","volume":"28","author":"S Lloyd","year":"1982","unstructured":"Lloyd, S.: Least squares quantization in PCM. IEEE Trans. Inf. Theory 28(2), 129\u2013137 (1982)","journal-title":"IEEE Trans. Inf. Theory"},{"key":"654_CR35","doi-asserted-by":"crossref","unstructured":"Ma, C., Yang, X., Zhang, C., Yang, M.H.: Long-term correlation tracking. In: IEEE CVPR, pp. 5388\u20135396 (2015)","DOI":"10.1109\/CVPR.2015.7299177"},{"key":"654_CR36","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/j.cviu.2016.05.011","volume":"150","author":"K Meshgi","year":"2016","unstructured":"Meshgi, K., ichi Maeda, S., Oba, S., Skibbe, H., zhe Li, Y., Ishii, S.: An occlusion-aware particle filter tracker to handle complex and persistent occlusions. Comput. Vis. Image Underst. 150, 81\u201394 (2016)","journal-title":"Comput. Vis. Image Underst."},{"key":"654_CR37","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/4175.001.0001","volume-title":"Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond","author":"B Scholkopf","year":"2001","unstructured":"Scholkopf, B., Smola, A.: Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. MIT Press, Cambridge (2001)"},{"issue":"7","key":"654_CR38","doi-asserted-by":"publisher","first-page":"1442","DOI":"10.1109\/TPAMI.2013.230","volume":"36","author":"A Smeulders","year":"2014","unstructured":"Smeulders, A., Chu, D., Cucchiara, R., Calderara, S., Dehghan, A., Shah, M.: Visual tracking: an experimental survey. IEEE Trans. Pattern Anal. Mach. Intell. 36(7), 1442\u20131468 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"654_CR39","doi-asserted-by":"crossref","unstructured":"Song, S., Xiao, J.: Tracking revisited using RGB-D camera: unified benchmark and baselines. In: IEEE ICCV, pp. 233\u2013240 (2013)","DOI":"10.1109\/ICCV.2013.36"},{"key":"654_CR40","doi-asserted-by":"crossref","unstructured":"Stalder, S., Grabner, H., Van\u00a0Gool, L.: Beyond semi-supervised tracking: tracking should be as simple as detection, but not simpler than recognition. In: IEEE ICCV Workshops, pp. 1409\u20131416 (2009)","DOI":"10.1109\/ICCVW.2009.5457445"},{"key":"654_CR41","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1016\/j.neucom.2013.10.021","volume":"131","author":"Q Wang","year":"2014","unstructured":"Wang, Q., Fang, J., Yuan, Y.: Multi-cue based tracking. Neurocomputing 131, 227\u2013236 (2014)","journal-title":"Neurocomputing"},{"key":"654_CR42","unstructured":"Weikersdorfer, D., Gossow, D., Beetz, M.: Depth-adaptive superpixels. In: ICPR, pp. 2087\u20132090 (2012)"},{"key":"654_CR43","doi-asserted-by":"crossref","unstructured":"Wu, Y., Lim, J., Yang, M.: Online object tracking: a benchmark. In: IEEE CVPR, pp. 2411\u20132418 (2013)","DOI":"10.1109\/CVPR.2013.312"},{"key":"654_CR44","doi-asserted-by":"crossref","unstructured":"Xu, G., Xu, X., Xing, X., Cai, B., Qing, C.: Multi-invariance appearance model for object tracking. In: IEEE DSP, pp. 347\u2013351 (2015)","DOI":"10.1109\/ICDSP.2015.7251890"},{"issue":"1","key":"654_CR45","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1109\/LSP.2015.2497460","volume":"23","author":"Y Xu","year":"2016","unstructured":"Xu, Y., Wang, J., Li, H., Li, Y., Miao, Z., Zhang, Y.: Patch-based scale calculation for real-time visual tracking. IEEE Signal Process. Lett. 23(1), 40\u201344 (2016)","journal-title":"IEEE Signal Process. Lett."},{"key":"654_CR46","doi-asserted-by":"publisher","first-page":"864","DOI":"10.1007\/978-3-642-33712-3_62","volume-title":"Computer Vision \u2013 ECCV 2012","author":"Kaihua Zhang","year":"2012","unstructured":"Zhang, K., Zhang, L., Yang, M.H.: Real-time compressive tracking. In: ECCV, pp. 864\u2013877 (2012)"},{"key":"654_CR47","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1007\/978-3-319-10602-1_9","volume-title":"Computer Vision \u2013 ECCV 2014","author":"Kaihua Zhang","year":"2014","unstructured":"Zhang, K., Zhang, L., Liu, Q., Zhang, D., Yang, M.H.: Fast visual tracking via dense spatio-temporal context learning. In: ECCV, pp. 127\u2013141 (2014)"},{"key":"654_CR48","doi-asserted-by":"crossref","unstructured":"Zhu, G., Wang, J., Wu, Y., Lu, H.: Collaborative correlation tracking. In: BMVC, pp. 184.1\u2013184.12 (2015)","DOI":"10.5244\/C.29.184"}],"container-title":["Journal of Real-Time Image Processing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11554-016-0654-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11554-016-0654-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11554-016-0654-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,12]],"date-time":"2025-06-12T21:07:37Z","timestamp":1749762457000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11554-016-0654-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,11,24]]},"references-count":48,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2019,10]]}},"alternative-id":["654"],"URL":"https:\/\/doi.org\/10.1007\/s11554-016-0654-3","relation":{},"ISSN":["1861-8200","1861-8219"],"issn-type":[{"value":"1861-8200","type":"print"},{"value":"1861-8219","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,11,24]]},"assertion":[{"value":"11 May 2016","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 November 2016","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 November 2016","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}