{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T15:38:27Z","timestamp":1773589107762,"version":"3.50.1"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T00:00:00Z","timestamp":1674432000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T00:00:00Z","timestamp":1674432000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Anhui Province Key Laboratory of Advanced Numerical Control & Servo Technology","award":["XJSK202102"],"award-info":[{"award-number":["XJSK202102"]}]},{"name":"Anhui Province Key Laboratory of Advanced Numerical Control & Servo Technology","award":["XJSK202102"],"award-info":[{"award-number":["XJSK202102"]}]},{"name":"Anhui Province Key Laboratory of Advanced Numerical Control & Servo Technology","award":["XJSK202102"],"award-info":[{"award-number":["XJSK202102"]}]},{"name":"Anhui Province Key Laboratory of Advanced Numerical Control & Servo Technology","award":["XJSK202102"],"award-info":[{"award-number":["XJSK202102"]}]},{"name":"the Natural Science Research Project of Higher Education of Anhui Province of China","award":["YJS20210446"],"award-info":[{"award-number":["YJS20210446"]}]},{"name":"the Natural Science Research Project of Higher Education of Anhui Province of China","award":["YJS20210446"],"award-info":[{"award-number":["YJS20210446"]}]},{"name":"the Natural Science Research Project of Higher Education of Anhui Province of China","award":["YJS20210446"],"award-info":[{"award-number":["YJS20210446"]}]},{"name":"the Special Fund for Collaborative Innovation of Anhui Polytechnic University & Jiujiang District","award":["2021CYXTB3"],"award-info":[{"award-number":["2021CYXTB3"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimedia Systems"],"published-print":{"date-parts":[[2023,6]]},"DOI":"10.1007\/s00530-023-01052-7","type":"journal-article","created":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T19:18:38Z","timestamp":1674501518000},"page":"1231-1244","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Adaptive Kalman Filter with power transformation for online multi-object tracking"],"prefix":"10.1007","volume":"29","author":[{"given":"Youyu","family":"Liu","sequence":"first","affiliation":[]},{"given":"Yi","family":"Li","sequence":"additional","affiliation":[]},{"given":"Dezhang","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Qingyan","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Wanbao","family":"Tao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,1,23]]},"reference":[{"key":"1052_CR1","doi-asserted-by":"crossref","unstructured":"Kishi, N., Shinkuma, R., Oka, M., et al.: Multi-object tracking for road surveillance without using features of image data. In: 2021 IEEE Global Communications Conference (GLOBECOM). pp. 1\u20136 (2021).","DOI":"10.1109\/GLOBECOM46510.2021.9686010"},{"issue":"14","key":"1052_CR2","doi-asserted-by":"publisher","first-page":"13776","DOI":"10.1109\/jsen.2022.3183502","volume":"22","author":"MME Yurtsever","year":"2022","unstructured":"Yurtsever, M.M.E., Eken, S.: BabyPose: real-time decoding of baby\u2019s non-verbal communication using 2D video-based pose estimation. IEEE Sens. J. 22(14), 13776\u201313784 (2022). https:\/\/doi.org\/10.1109\/jsen.2022.3183502","journal-title":"IEEE Sens. J."},{"issue":"20","key":"1052_CR3","doi-asserted-by":"publisher","first-page":"2479","DOI":"10.3390\/electronics10202479","volume":"10","author":"J Chen","year":"2021","unstructured":"Chen, J., Wang, F., Li, C., et al.: Online multiple object tracking using a novel discriminative module for autonomous driving. Electronics 10(20), 2479 (2021). https:\/\/doi.org\/10.3390\/electronics10202479","journal-title":"Electronics"},{"key":"1052_CR4","unstructured":"Ge, Z., Liu, S., Wang, F., et al.: YOLOX: Exceeding YOLO Series in 2021. (2021). https:\/\/ui.adsabs.harvard.edu\/abs\/2021arXiv210708430G"},{"key":"1052_CR5","unstructured":"Zhou, X., Wang, D., Kr\u00e4henb\u00fchl, P. J. a. e.-p.: Objects as Points. (2019). https:\/\/ui.adsabs.harvard.edu\/abs\/2019arXiv190407850Z"},{"issue":"11","key":"1052_CR6","doi-asserted-by":"publisher","first-page":"3053","DOI":"10.1007\/s13042-020-01220-5","volume":"12","author":"I Ahmed","year":"2021","unstructured":"Ahmed, I., Ahmad, M., Ahmad, A., et al.: Top view multiple people tracking by detection using deep SORT and YOLOv3 with transfer learning: within 5G infrastructure. Int. J. Mach. Learn. Cybern. 12(11), 3053\u20133067 (2021)","journal-title":"Int. J. Mach. Learn. Cybern."},{"issue":"3","key":"1052_CR7","doi-asserted-by":"publisher","first-page":"925","DOI":"10.1007\/s00530-022-00895-w","volume":"28","author":"W Guo","year":"2022","unstructured":"Guo, W., Jin, Y., Shan, B., et al.: Multi-cue multi-hypothesis tracking with re-identification for multi-object tracking. Multimed. Syst. 28(3), 925\u2013937 (2022)","journal-title":"Multimed. Syst."},{"issue":"12","key":"1052_CR8","doi-asserted-by":"publisher","first-page":"3660","DOI":"10.1109\/TCSVT.2018.2881123","volume":"29","author":"H Sheng","year":"2018","unstructured":"Sheng, H., Chen, J., Zhang, Y., et al.: Iterative multiple hypothesis tracking with tracklet-level association. IEEE Trans. Cir. Syst. Video Technol. 29(12), 3660\u20133672 (2018)","journal-title":"IEEE Trans. Cir. Syst. Video Technol."},{"key":"1052_CR9","doi-asserted-by":"crossref","unstructured":"Song, Y.-m., Jeon, M.: Online multiple object tracking with the hierarchically adopted gm-phd filter using motion and appearance. In: 2016 IEEE International conference on consumer electronics-Asia (ICCE-Asia). pp. 1\u20134 (2016)","DOI":"10.1109\/ICCE-Asia.2016.7804800"},{"key":"1052_CR10","doi-asserted-by":"crossref","unstructured":"Wang, Z., Zheng, L., Liu, Y., et al.: Towards real-time multi-object tracking. In: European Conference on Computer Vision. pp. 107\u2013122 (2020)","DOI":"10.1007\/978-3-030-58621-8_7"},{"issue":"11","key":"1052_CR11","doi-asserted-by":"publisher","first-page":"3069","DOI":"10.1007\/s11263-021-01513-4","volume":"129","author":"Y Zhang","year":"2021","unstructured":"Zhang, Y., Wang, C., Wang, X., et al.: Fairmot: on the fairness of detection and re-identification in multiple object tracking. Int. J. Comput. Vision 129(11), 3069\u20133087 (2021)","journal-title":"Int. J. Comput. Vision"},{"key":"1052_CR12","doi-asserted-by":"crossref","unstructured":"Pang, J., Qiu, L., Li, X., et al.: Quasi-dense similarity learning for multiple object tracking. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 164\u2013173 (2021).","DOI":"10.1109\/CVPR46437.2021.00023"},{"key":"1052_CR13","doi-asserted-by":"crossref","unstructured":"Zhou, X., Koltun, V., Kr\u00e4henb\u00fchl, P.: Tracking objects as points. In: European Conference on Computer Vision. pp. 474\u2013490 (2020).","DOI":"10.1007\/978-3-030-58548-8_28"},{"issue":"6","key":"1052_CR14","doi-asserted-by":"publisher","first-page":"4076","DOI":"10.1007\/s11227-017-2202-8","volume":"76","author":"W Hua","year":"2017","unstructured":"Hua, W., Mu, D., Zheng, Z., et al.: Online multi-person tracking assist by high-performance detection. J. Supercomput. 76(6), 4076\u20134094 (2017). https:\/\/doi.org\/10.1007\/s11227-017-2202-8","journal-title":"J. Supercomput."},{"key":"1052_CR15","doi-asserted-by":"crossref","unstructured":"Chen, L., Ai, H., Zhuang, Z., et al.: Real-time multiple people tracking with deeply learned candidate selection and person re-identification. In: 2018 IEEE International Conference on Multimedia and Expo (ICME). pp. 1\u20136 (2018).","DOI":"10.1109\/ICME.2018.8486597"},{"key":"1052_CR16","doi-asserted-by":"crossref","unstructured":"Wojke, N., Bewley, A., Paulus, D.: Simple online and realtime tracking with a deep association metric. In: 2017 IEEE International Conference on Image Processing (ICIP). pp. 3645\u20133649 (2017).","DOI":"10.1109\/ICIP.2017.8296962"},{"issue":"12","key":"1052_CR17","doi-asserted-by":"publisher","first-page":"5667","DOI":"10.1109\/TIP.2017.2745103","volume":"26","author":"Y Min","year":"2017","unstructured":"Min, Y., Yuwei, W., Yunde, J.: A hybrid data association framework for robust online multi-object tracking. IEEE Trans. Image Process. 26(12), 5667\u20135679 (2017). https:\/\/doi.org\/10.1109\/TIP.2017.2745103","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"1052_CR18","doi-asserted-by":"publisher","first-page":"595","DOI":"10.1109\/TPAMI.2017.2691769","volume":"40","author":"SH Bae","year":"2018","unstructured":"Bae, S.H., Yoon, K.J.: Confidence-based data association and discriminative deep appearance learning for robust online multi-object tracking. IEEE Trans. Pattern Anal. Mach. Intell. 40(3), 595\u2013610 (2018). https:\/\/doi.org\/10.1109\/TPAMI.2017.2691769","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1052_CR19","unstructured":"Zhang, Y., Sun, P., Jiang, Y., et al.: ByteTrack: Multi-Object Tracking by Associating Every Detection Box (2021). https:\/\/ui.adsabs.harvard.edu\/abs\/2021arXiv211006864Z"},{"issue":"1","key":"1052_CR20","first-page":"35","volume":"82","author":"RE Kalman","year":"1960","unstructured":"Kalman, R.E.: A new approach to linear filtering and prediction problems. J Fluids Eng. 82(1), 35\u201345 (1960)","journal-title":"J Fluids Eng."},{"key":"1052_CR21","doi-asserted-by":"crossref","unstructured":"Bewley, A., Ge, Z., Ott, L., et al.: Simple online and realtime tracking. In: 2016 IEEE International Conference on Image Processing (ICIP). pp. 3464\u20133468 (2016).","DOI":"10.1109\/ICIP.2016.7533003"},{"key":"1052_CR22","doi-asserted-by":"crossref","unstructured":"Hou, X., Wang, Y., Chau, L.-P.: Vehicle tracking using deep sort with low confidence track filtering. In: 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS). pp. 1\u20136 (2019).","DOI":"10.1109\/AVSS.2019.8909903"},{"key":"1052_CR23","first-page":"20230","volume":"34","author":"J He","year":"2021","unstructured":"He, J., Erfani, S., Ma, X., et al.: Alpha-IoU: a family of power intersection over union losses for bounding box regression. Adv. Neural. Inf. Process. Syst. 34, 20230\u201320242 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"1052_CR24","doi-asserted-by":"crossref","unstructured":"Du, Y., Wan, J., Zhao, Y., et al.: GIAOTracker: A comprehensive framework for MCMOT with global information and optimizing strategies in VisDrone 2021. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision. pp. 2809\u20132819 (2021).","DOI":"10.1109\/ICCVW54120.2021.00315"},{"issue":"4","key":"1052_CR25","doi-asserted-by":"publisher","first-page":"6329","DOI":"10.1007\/s11042-020-10004-6","volume":"80","author":"K Sarkar","year":"2021","unstructured":"Sarkar, K., Halder, T.K., Mandal, A.: Adaptive power-law and cdf based geometric transformation for low contrast image enhancement. Multimed. Tools Appl. 80(4), 6329\u20136353 (2021)","journal-title":"Multimed. Tools Appl."},{"key":"1052_CR26","unstructured":"Milan, A., Leal-Taixe, L., Reid, I., et al.: MOT16: A Benchmark for Multi-Object Tracking (2016). https:\/\/ui.adsabs.harvard.edu\/abs\/2016arXiv160300831M"},{"key":"1052_CR27","unstructured":"Lin, W., Liu, H., Liu, S., et al.: Human in Events: A Large-Scale Benchmark for Human-centric Video Analysis in Complex Events (2020). https:\/\/ui.adsabs.harvard.edu\/abs\/2020arXiv200504490L"},{"key":"1052_CR28","doi-asserted-by":"crossref","unstructured":"Lu, Z., Rathod, V., Votel, R., et al.: Retinatrack: Online single stage joint detection and tracking. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 14668\u201314678 (2020).","DOI":"10.1109\/CVPR42600.2020.01468"},{"key":"1052_CR29","unstructured":"Sener, O., Koltun, V.: Multi-task learning as multi-objective optimization. In: the 32nd Conference on Neural Information Processing Systems (NeurIPS 2018). (2018)."},{"key":"1052_CR30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2020.3040221","volume":"60","author":"J Zhang","year":"2021","unstructured":"Zhang, J., Xing, M., Sun, G.-C., et al.: Multiple statistics contributing to few-sample deep learning for subtle trace detection in high-resolution SAR images. IEEE Trans. Geosci. Remote Sens. 60, 1\u201314 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"15","key":"1052_CR31","doi-asserted-by":"publisher","first-page":"4126","DOI":"10.3390\/s20154126","volume":"20","author":"T Kim","year":"2020","unstructured":"Kim, T., Park, T.-H.: Extended Kalman filter (EKF) design for vehicle position tracking using reliability function of radar and lidar. Sensors. 20(15), 4126 (2020)","journal-title":"Sensors."},{"issue":"5","key":"1052_CR32","doi-asserted-by":"publisher","first-page":"607","DOI":"10.1007\/s12204-021-2350-0","volume":"26","author":"M Wang","year":"2021","unstructured":"Wang, M., Wu, X.: Multi-object tracking strategy of autonomous vehicle using modified unscented Kalman Filter and reference point switching. J. Shanghai Jiaotong University (Science). 26(5), 607\u2013614 (2021)","journal-title":"J. Shanghai Jiaotong University (Science)."},{"key":"1052_CR33","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1016\/j.neucom.2019.03.077","volume":"351","author":"Y Cui","year":"2019","unstructured":"Cui, Y., Zhang, J., He, Z., et al.: Multiple pedestrian tracking by combining particle filter and network flow model. Neurocomputing 351, 217\u2013227 (2019)","journal-title":"Neurocomputing"},{"key":"1052_CR34","doi-asserted-by":"publisher","DOI":"10.1155\/2015\/573131","author":"W Guo","year":"2015","unstructured":"Guo, W., Zhao, Q., Gu, D.: Visual tracking using an insect vision embedded particle filter. Math. Prob. Eng. (2015). https:\/\/doi.org\/10.1155\/2015\/573131","journal-title":"Math. Prob. Eng."},{"issue":"11","key":"1052_CR35","doi-asserted-by":"publisher","first-page":"2294","DOI":"10.3390\/app8112294","volume":"8","author":"AS Khattak","year":"2018","unstructured":"Khattak, A.S., Raja, G., Anjum, N.: Adaptive framework for multi-feature hybrid object tracking. Appl. Sci. 8(11), 2294 (2018)","journal-title":"Appl. Sci."},{"key":"1052_CR36","doi-asserted-by":"crossref","unstructured":"Zhai, G., Wu, C., Wang, Y.: Millimeter wave radar target tracking based on adaptive Kalman filter. In: 2018 IEEE Intelligent Vehicles Symposium (IV). pp. 453\u2013458 (2018).","DOI":"10.1109\/IVS.2018.8500505"},{"key":"1052_CR37","doi-asserted-by":"publisher","first-page":"222918","DOI":"10.1109\/ACCESS.2020.3043878","volume":"8","author":"Y Wang","year":"2020","unstructured":"Wang, Y., Mu, X.: Dynamic siamese network with adaptive Kalman filter for object tracking in complex scenes. IEEE Access. 8, 222918\u2013222930 (2020)","journal-title":"IEEE Access."},{"key":"1052_CR38","unstructured":"Cao, J., Weng, X., Khirodkar, R., et al.: Observation-centric SORT: rethinking SORT for robust multi-object tracking. (2022). https:\/\/ui.adsabs.harvard.edu\/abs\/2022arXiv220314360C"},{"issue":"5","key":"1052_CR39","doi-asserted-by":"publisher","first-page":"827","DOI":"10.1007\/s11760-017-1224-2","volume":"12","author":"M Kumar","year":"2018","unstructured":"Kumar, M., Singh, K.: Retrieval of head\u2013neck medical images using Gabor filter based on power-law transformation method and rank BHMT. Signal Image Video Process. 12(5), 827\u2013833 (2018)","journal-title":"Signal Image Video Process."},{"key":"1052_CR40","doi-asserted-by":"crossref","unstructured":"Lin, T.-Y., Goyal, P., Girshick, R., et al.: Focal loss for dense object detection. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 2980\u20132988 (2017).","DOI":"10.1109\/ICCV.2017.324"},{"key":"1052_CR41","unstructured":"Dendorfer, P., Rezatofighi, H., Milan, A., et al.: MOT20: a benchmark for multi object tracking in crowded scenes. (2020). https:\/\/ui.adsabs.harvard.edu\/abs\/2020arXiv200309003D"},{"key":"1052_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2008\/246309","volume":"2008","author":"K Bernardin","year":"2008","unstructured":"Bernardin, K., Stiefelhagen, R.: Evaluating multiple object tracking performance: the clear mot metrics. EURASIP J. Image Video Process. 2008, 1\u201310 (2008)","journal-title":"EURASIP J. Image Video Process."},{"key":"1052_CR43","doi-asserted-by":"crossref","unstructured":"Ristani, E., Solera, F., Zou, R., et al.: Performance measures and a data set for multi-target, multi-camera tracking. In: European conference on computer vision. pp. 17\u201335 (2016).","DOI":"10.1007\/978-3-319-48881-3_2"},{"issue":"2","key":"1052_CR44","doi-asserted-by":"publisher","first-page":"548","DOI":"10.1007\/s11263-020-01375-2","volume":"129","author":"J Luiten","year":"2021","unstructured":"Luiten, J., Os Ep, A.A., Dendorfer, P., et al.: HOTA: a higher order metric for evaluating multi-object tracking. Int. J. Comput. Vis. 129(2), 548\u2013578 (2021). https:\/\/doi.org\/10.1007\/s11263-020-01375-2","journal-title":"Int. J. Comput. Vis."},{"key":"1052_CR45","unstructured":"Wu, B., Nevatia, R.: Tracking of multiple, partially occluded humans based on static body part detection. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06). pp. 951\u2013958 (2006)."},{"key":"1052_CR46","doi-asserted-by":"publisher","unstructured":"Shao, S., Zhao, Z., Li, B., et al.: Crowdhuman: a benchmark for detecting human in a crowd. (2018). https:\/\/doi.org\/10.48550\/arXiv.1805.00123","DOI":"10.48550\/arXiv.1805.00123"},{"key":"1052_CR47","doi-asserted-by":"crossref","unstructured":"Zhang, S., Benenson, R., Schiele, B.: Citypersons: a diverse dataset for pedestrian detection. In: Proceedings of the IEEE Conference on Computer VISION and Pattern Recognition. pp. 3213\u20133221 (2017)","DOI":"10.1109\/CVPR.2017.474"},{"key":"1052_CR48","doi-asserted-by":"crossref","unstructured":"Ess, A., Leibe, B., Schindler, K., et al.: A mobile vision system for robust multi-person tracking. In: 2008 IEEE Conference on Computer Vision and Pattern Recognition. pp. 1\u20138 (2008)","DOI":"10.1109\/CVPR.2008.4587581"},{"key":"1052_CR49","doi-asserted-by":"crossref","unstructured":"Shuai, B., Berneshawi, A., Wang, M., et al.: Application of multi-object tracking with Siamese track-RCNN to the human in events dataset. In: Proceedings of the 28th ACM International Conference on Multimedia. pp. 4625\u20134629 (2020)","DOI":"10.1145\/3394171.3416297"}],"container-title":["Multimedia Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-023-01052-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00530-023-01052-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-023-01052-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,30]],"date-time":"2023-05-30T14:15:49Z","timestamp":1685456149000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00530-023-01052-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,23]]},"references-count":49,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2023,6]]}},"alternative-id":["1052"],"URL":"https:\/\/doi.org\/10.1007\/s00530-023-01052-7","relation":{},"ISSN":["0942-4962","1432-1882"],"issn-type":[{"value":"0942-4962","type":"print"},{"value":"1432-1882","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,23]]},"assertion":[{"value":"11 September 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 January 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 January 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This paper does not contain any studies with human or animal subjects and all authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}