{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:23:43Z","timestamp":1740122623194,"version":"3.37.3"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2019,5,6]],"date-time":"2019-05-06T00:00:00Z","timestamp":1557100800000},"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":["Appl Intell"],"published-print":{"date-parts":[[2019,11]]},"DOI":"10.1007\/s10489-019-01480-x","type":"journal-article","created":{"date-parts":[[2019,5,6]],"date-time":"2019-05-06T16:26:32Z","timestamp":1557159992000},"page":"3864-3880","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Research on scale adaptive particle filter tracker with feature integration"],"prefix":"10.1007","volume":"49","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7066-3454","authenticated-orcid":false,"given":"Yuqi","family":"Xiao","sequence":"first","affiliation":[]},{"given":"Difu","family":"Pan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,5,6]]},"reference":[{"key":"1480_CR1","doi-asserted-by":"crossref","unstructured":"Danelljan M, Bhat G, Khan FS, et al (2017) ECO: Efficient Convolution Operators for Tracking,. 2017 IEEE Conference on Computer Vision and Pattern Recognition","DOI":"10.1109\/CVPR.2017.733"},{"key":"1480_CR2","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1016\/j.ins.2019.02.065","volume":"486","author":"H Fujita","year":"2019","unstructured":"Fujita H, Cimr D (2019) Computer aided detection for fibrillations and flutters using deep convolutional neural network. Inf Sci 486:231\u2013239","journal-title":"Inf Sci"},{"key":"1480_CR3","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1016\/j.eswa.2017.04.003","volume":"82","author":"Z Chongsheng","year":"2017","unstructured":"Chongsheng Z, Changchang L, Xiangliang Z, George A (2017) An up-to-date comparison of state-of-the-art classification algorithms. Expert Syst Appl 82:128\u2013150","journal-title":"Expert Syst Appl"},{"key":"1480_CR4","doi-asserted-by":"crossref","unstructured":"Gonczarek A, Tomczak JM (2016) Articulated tracking with manifold regularized particle filter. Springer-Verlag New York, Inc.","DOI":"10.1007\/s00138-016-0748-8"},{"issue":"3","key":"1480_CR5","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1049\/iet-cvi.2013.0004","volume":"8","author":"X An","year":"2014","unstructured":"An X, Kim J, Han Y (2014) Optimal colour-based mean shift algorithm for tracking objects. IET Comput Vis 8(3):235\u2013244","journal-title":"IET Comput Vis"},{"issue":"6","key":"1480_CR6","doi-asserted-by":"publisher","first-page":"3145","DOI":"10.1007\/s11042-014-2427-y","volume":"75","author":"Z Zhou","year":"2016","unstructured":"Zhou Z, Zhou M, Shi X (2016) Target tracking based on foreground probability. Multimed Tools Appl 75(6):3145\u20133160","journal-title":"Multimed Tools Appl"},{"issue":"5","key":"1480_CR7","doi-asserted-by":"publisher","first-page":"199","DOI":"10.5772\/54047","volume":"9","author":"Xiaoyong Zhang","year":"2012","unstructured":"Zhang X, Peng J, Yu W, Lin KC (2012) Confidence-level-based new adaptive particle filter for nonlinear object tracking. Int J Adv Robot Syst 9(1)","journal-title":"International Journal of Advanced Robotic Systems"},{"issue":"8","key":"1480_CR8","doi-asserted-by":"publisher","first-page":"3944","DOI":"10.1016\/j.eswa.2013.12.031","volume":"41","author":"T Li","year":"2013","unstructured":"Li T, Sun S, Sattar TP, Corchado JM (2013) Fight sample degeneracy and impoverishment in particle filters: a review of intelligent approaches. Expert Syst Appl 41(8):3944\u20133954","journal-title":"Expert Syst Appl"},{"issue":"11","key":"1480_CR9","doi-asserted-by":"publisher","first-page":"959","DOI":"10.1049\/iet-ipr.2014.0666","volume":"9","author":"SD Lin","year":"2015","unstructured":"Lin SD, Lin JJ, Chuang CY (2015) Particle filter with occlusion handling for visual tracking. Image Processing IET 9(11):959\u2013968","journal-title":"Image Processing IET"},{"issue":"5","key":"1480_CR10","doi-asserted-by":"publisher","first-page":"440","DOI":"10.1049\/iet-ipr.2009.0126","volume":"5","author":"P Chen","year":"2011","unstructured":"Chen P, Qian H, Wang W, Zhu M (2011) Contour tracking using Gaussian particle filter. IET Image Process 5(5):440\u2013447","journal-title":"IET Image Process"},{"key":"1480_CR11","doi-asserted-by":"publisher","first-page":"426","DOI":"10.1007\/978-3-319-02895-8_38","volume-title":"International Conference on Advanced Concepts for Intelligent Vision Systems","author":"B Rymut","year":"2013","unstructured":"Rymut B, Kwolek B, Krzeszowski T (2013) GPU-accelerated human motion tracking using particle filter combined with PSO. In: International Conference on Advanced Concepts for Intelligent Vision Systems. Springer-Verlag, New York, pp 426\u2013437"},{"key":"1480_CR12","first-page":"2","volume":"2015","author":"J Yang","year":"2015","unstructured":"Yang J et al (2015) Fast Object Tracking Employing Labelled Particle Filter for Thermal Infrared Imager. International Journal of Distributed Sensor Networks 2015:2","journal-title":"International Journal of Distributed Sensor Networks"},{"issue":"5","key":"1480_CR13","doi-asserted-by":"publisher","first-page":"2502","DOI":"10.1109\/TNS.2016.2590505","volume":"63","author":"Q Wei","year":"2016","unstructured":"Wei Q, Dai T, Ma T, Liu Y, Gu Y (2016) Crystal identification in dual-layer-offset doi-pet detectors using stratified peak tracking based on svd and mean-shift algorithm. IEEE Trans Nucl Sci 63(5):2502\u20132508","journal-title":"IEEE Trans Nucl Sci"},{"issue":"1","key":"1480_CR14","doi-asserted-by":"publisher","first-page":"017204","DOI":"10.1117\/1.3281669","volume":"49","author":"Xiangyang Wang","year":"2010","unstructured":"Wang X et al (2010) Annealed particle filter based on particle swarm optimization for articulated three-dimensional human motion tracking. Opt Eng 49(1)","journal-title":"Optical Engineering"},{"key":"1480_CR15","first-page":"710","volume":"24","author":"CH Dai","year":"2006","unstructured":"Dai CH, Zhu YF, Chen WR (2006) Adaptive probabilities of crossover and mutation in genetic algorithms based on cloud model. Information Theory Workshop, 2006. ITW '06 Chengdu. IEEE 24:710\u2013713","journal-title":"IEEE"},{"issue":"1","key":"1480_CR16","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1023\/A:1012815625611","volume":"16","author":"TP Hong","year":"2002","unstructured":"Hong TP, Wang HS, Lin WY, Lee WY (2002) Evolution of appropriate crossover and mutation operators in a genetic process. Appl Intell 16(1):7\u201317","journal-title":"Appl Intell"},{"issue":"9","key":"1480_CR17","doi-asserted-by":"publisher","first-page":"2435","DOI":"10.1109\/TITS.2016.2641903","volume":"18","author":"R Mallah","year":"2017","unstructured":"Mallah R, Quintero A, Farooq B (2017) Distributed classification of urban congestion using VANET. IEEE Trans Intell Transp Syst 18(9):2435\u20132442","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"12","key":"1480_CR18","doi-asserted-by":"publisher","first-page":"794","DOI":"10.1049\/iet-ipr.2014.0238","volume":"8","author":"MM Azab","year":"2014","unstructured":"Azab MM, Shedeed HA, Hussein AS (2014) New technique for online object tracking-by-detection in video. IET Image Process 8(12):794\u2013803","journal-title":"IET Image Process"},{"issue":"6","key":"1480_CR19","first-page":"1454","volume":"18","author":"G Tanzmeister","year":"2017","unstructured":"Tanzmeister G, Wollherr D (2017) Evidential grid-based tracking and mapping. IEEE Trans Intell Transp Syst 18(6):1454\u20131467","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"10","key":"1480_CR20","doi-asserted-by":"publisher","first-page":"5519","DOI":"10.1109\/TSP.2012.2205569","volume":"60","author":"YS Shmaliy","year":"2012","unstructured":"Shmaliy YS (2012) Suboptimal FIR filtering of nonlinear models in additive white Gaussian noise. IEEE Trans Signal Process 60(10):5519\u20135527","journal-title":"IEEE Trans Signal Process"},{"issue":"1","key":"1480_CR21","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1049\/iet-cvi.2009.0075","volume":"6","author":"J Ning","year":"2010","unstructured":"Ning J, Zhang L, Zhang D, Wu C (2010) Robust mean-shift tracking with corrected background-weighted histogram. IET Comput Vis 6(1):62\u201369","journal-title":"IET Comput Vis"},{"issue":"2","key":"1480_CR22","doi-asserted-by":"publisher","first-page":"020503-1","DOI":"10.1117\/1.3314310","volume":"49","author":"J Sun","year":"2010","unstructured":"Sun J (2010) Object tracking using an adaptive Kalman filter combined with mean shift. Opt Eng 49(2):020503-1\u2013020503-3","journal-title":"Opt Eng"},{"key":"1480_CR23","first-page":"1150","volume":"2","author":"DG Lowe","year":"1999","unstructured":"Lowe DG (1999) Object Recognition from Local Scale-Invariant Features. ICCV IEEE Computer Society 2:1150","journal-title":"ICCV IEEE Computer Society"},{"key":"1480_CR24","doi-asserted-by":"publisher","first-page":"472","DOI":"10.1007\/978-3-319-46454-1_29","volume-title":"Computer Vision \u2013 ECCV 2016","author":"Martin Danelljan","year":"2016","unstructured":"Danelljan M, Robinson A., Khan FS, Felsberg M (2016) Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking,\u201d European Conference on Computer Vision. Springer, Cham. 472-488"},{"key":"1480_CR25","doi-asserted-by":"crossref","unstructured":"Danelljan M, H\u00e4ger G, Khan FS, Felsberg M (2016) Adaptive Decontamination of the Training Set: A Unified Formulation for Discriminative Visual Tracking. Computer Vision and Pattern Recognition. IEEE:1430\u20131438","DOI":"10.1109\/CVPR.2016.159"},{"key":"1480_CR26","doi-asserted-by":"crossref","unstructured":"Hong Z, Chen Z, Wang C et al (2015) MUlti-Store Tracker (MUSTer): A cognitive psychology inspired approach to object tracking. Computer Vision and Pattern Recognition. IEEE:749\u2013758","DOI":"10.1109\/CVPR.2015.7298675"},{"key":"1480_CR27","doi-asserted-by":"crossref","unstructured":"Galoogahi HK, Fagg A, Lucey S (2017) Learning Background-Aware Correlation Filters for Visual Tracking. IEEE Computer Society:1144\u20131152","DOI":"10.1109\/ICCV.2017.129"},{"key":"1480_CR28","doi-asserted-by":"crossref","unstructured":"Wang M, Liu Y, Huang Z (2017) Large Margin Object Tracking with Circulant Feature Maps. IEEE Computer Society:4800\u20134808","DOI":"10.1109\/CVPR.2017.510"},{"issue":"2","key":"1480_CR29","first-page":"1401","volume":"38","author":"L Bertinetto","year":"2015","unstructured":"Bertinetto L, Valmadre J, Golodetz S, Miksik O, Torr P (2015) Staple: complementary learners for real-time tracking. Proc IEEE Conf Comput Vis Pattern Recognit 38(2):1401\u20131409","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"1480_CR30","unstructured":"Li Y, Zhu J (2014) A Scale Adaptive Kernel Correlation Filter Tracker with Feature Integration. ECCV Workshops"},{"key":"1480_CR31","doi-asserted-by":"crossref","unstructured":"Danelljan M, H\u00e4ger G, Khan FS, Felsberg M (2014) Accurate Scale Estimation for Robust Visual Tracking. British Machine Vision Conference:65.1\u201365.11","DOI":"10.5244\/C.28.65"},{"key":"1480_CR32","first-page":"2411","volume":"9","author":"Y Wu","year":"2013","unstructured":"Wu Y, Lim J, Yang MH (2013) Online object tracking: a benchmark. Proc IEEE Computer Vision and Pattern Recognition 9:2411\u20132418","journal-title":"Proc IEEE Computer Vision and Pattern Recognition"},{"key":"1480_CR33","unstructured":"Kristan M, Leonardis A, Matas J, Felsberg M, Pflugfelder R, \u010cehovin L et al (2016) The visual object tracking vot2016 challenge results. In: ECCV workshop"},{"key":"1480_CR34","unstructured":"Nam H, Baek M, Han B (2016) Modeling and propagating CNNS in a tree structure for visual tracking. arXiv preprint arXiv:1608.07242"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-019-01480-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10489-019-01480-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-019-01480-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,4]],"date-time":"2020-05-04T23:23:47Z","timestamp":1588634627000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10489-019-01480-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,6]]},"references-count":34,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2019,11]]}},"alternative-id":["1480"],"URL":"https:\/\/doi.org\/10.1007\/s10489-019-01480-x","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"type":"print","value":"0924-669X"},{"type":"electronic","value":"1573-7497"}],"subject":[],"published":{"date-parts":[[2019,5,6]]},"assertion":[{"value":"6 May 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}