Real-time object tracking based on an adaptive transition model and extended Kalman filter to handle full occlusion
Author:
Funder
Yazd University
Publisher
Springer Science and Business Media LLC
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software
Link
http://link.springer.com/content/pdf/10.1007/s00371-019-01652-3.pdf
Reference40 articles.
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2. Yilmaz, A., Javed, O., Shah, M.: Object tracking: a survey. ACM Comput. Surv (CSUR) 38, 13 (2006)
3. Liu, T., Wang, G., Yang, Q.: Real-time part-based visual tracking via adaptive correlation filters. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4902–4912 (2015)
4. Liu, Q., Zhao, X., Hou, Z.: Survey of single-target visual tracking methods based on online learning. IET Comput. Vision 8, 419–428 (2014)
5. Wu, Y., Lim, J., Yang, M.-H.: Object tracking benchmark. IEEE Trans. Pattern Anal. Mach. Intell. 37, 1834–1848 (2015)
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