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Visual Tracking Based on Sparse Representation

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Abstract

Appearance change caused by intrinsic and extrinsic factors is a challenging problem in online object tracking.

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Notes

  1. 1.

    ©2014 IEEE, Reprinted, with permission, from Ref. [12].

  2. 2.

    ©2012 IEEE, Reprinted, with permission, from Ref. [2].

References

  1. Gao, S., Tsang, I.W., Chia, L., Zhao, P.: Local features are not lonely—laplacian sparse coding for image classification. In: The Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, pp. 3555–3561 (2010)

    Google Scholar 

  2. Jia, X., Lu, H., Yang, M.: Visual tracking via adaptive structural local sparse appearance model. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1822–1829 (2012)

    Google Scholar 

  3. Kalal, Z., Mikolajczyk, K., Matas, J.: Tracking-learning-detection. IEEE Trans. Pattern Anal. Mach. Intell. 34(7), 1409–1422 (2012)

    Article  Google Scholar 

  4. Liu, B., Huang, J., Yang, L., Kulikowski, C.A.: Robust tracking using local sparse appearance model and k-selection. In: The 24th IEEE Conference on Computer Vision and Pattern Recognition, pp. 1313–1320 (2011)

    Google Scholar 

  5. Liu, B., Yang, L., Huang, J., Meer, P., Gong, L., Kulikowski, C.A.: Robust and fast collaborative tracking with two stage sparse optimization. In: 11th European Conference on Computer Vision, ECCV 2010, pp. 624–637 (2010)

    Chapter  Google Scholar 

  6. Matthews, I.A., Ishikawa, T., Baker, S.: The template update problem. IEEE Trans. Pattern Anal. Mach. Intell. 26(6), 810–815 (2004)

    Article  Google Scholar 

  7. Mei, X., Ling, H.: Robust visual tracking using \({\ell }_1\) minimization. In: IEEE 12th International Conference on Computer Vision, pp. 1436–1443 (2009)

    Google Scholar 

  8. Ross, D.A., Lim, J., Lin, R., Yang, M.: Incremental learning for robust visual tracking. Int. J. Comput. Vis. 77(1–3), 125–141 (2008)

    Article  Google Scholar 

  9. Santner, J., Leistner, C., Saffari, A., Pock, T., Bischof, H.: PROST: parallel robust online simple tracking. In: The Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, pp. 723–730 (2010)

    Google Scholar 

  10. Wright, J., Yang, A.Y., Ganesh, A., Sastry, S.S., Ma, Y.: Robust face recognition via sparse representation. IEEE Trans. Pattern Anal. Mach. Intell. 31(2), 210–227 (2009)

    Article  Google Scholar 

  11. Wu, Y., Lim, J., Yang, M.: Object tracking benchmark. IEEE Trans. Pattern Anal. Mach. Intell. 37(9), 1834–1848 (2015)

    Article  Google Scholar 

  12. Zhong, W., Lu, H., Yang, M.: Robust object tracking via sparse collaborative appearance model. IEEE Trans. Pattern Anal. Mach. Intell. 23(5), 2356–2368 (2014)

    MathSciNet  MATH  Google Scholar 

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Correspondence to Huchuan Lu .

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Lu, H., Wang, D. (2019). Visual Tracking Based on Sparse Representation. In: Online Visual Tracking. Springer, Singapore. https://doi.org/10.1007/978-981-13-0469-9_2

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  • DOI: https://doi.org/10.1007/978-981-13-0469-9_2

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  • Online ISBN: 978-981-13-0469-9

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