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Covariance-based online validation of video tracking

Covariance-based online validation of video tracking

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A novel approach is proposed for online evaluation of video tracking without ground-truth data. The temporal evolution of the covariance features is exploited to detect the stability of the tracker output over time. A model validation strategy performs such detection without learning the failure cases of the tracker under evaluation. Then, the tracker performance is estimated by a finite state machine determining whether the tracker is on-target (successful) or not (unsuccessful). The experimental results over a heterogeneous dataset show that the proposed approach outperforms related state-of-the-art approaches in terms of performance and computational cost.

References

    1. 1)
    2. 2)
      • J. SanMiguel , A. Cavallaro .
        2. SanMiguel, J., Cavallaro, A.: ‘Temporal validation of particle filters for video tracking’, Comput. Vis. Image Underst., 2014, 131, (0), pp. 4255.
        . Comput. Vis. Image Underst. , 0 , 42 - 55
    3. 3)
    4. 4)
    5. 5)
      • C. Spampinato , S. Palazzo , D. Giordano .
        5. Spampinato, C., Palazzo, S., Giordano, D.: ‘Evaluation of tracking algorithm performance without ground-truth data’. Proc. of IEEE Conf. on Image Processing, Orlando, FL, USA, October 2012, pp. 13451348.
        . Proc. of IEEE Conf. on Image Processing , 1345 - 1348
    6. 6)
    7. 7)
    8. 8)
      • 8. SOVTds: a single-object video tracking dataset’. Available at http://www-vpu.eps.uam.es/SOVTds/, accessed October 2014.
        .
    9. 9)
    10. 10)
    11. 11)
    12. 12)
    13. 13)
    14. 14)
      • S. Oron , A. Bar , D. Levi , S. Avidan .
        14. Oron, S., Bar, A., Levi, D., Avidan, S.: ‘Locally orderless tracking’, Int. J. Comput. Vis., 2014. Available at http://www.dx.doi.org/10.1007/s11263-014-0740-6, accessed October 2014.
        . Int. J. Comput. Vis.
    15. 15)
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