CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 2010 vol.32 Issue No.02 - February

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Issue No.02 - February (2010 vol.32)

pp: 274-287

Qi Zhao , University of California, Santa Cruz, Santa Cruz

Zhi Yang , University of California, Santa Cruz, Santa Cruz

Hai Tao , University of California, Santa Cruz, Santa Cruz

ABSTRACT

The Earth Mover's Distance (EMD) is a similarity measure that captures perceptual difference between two distributions. Its computational complexity, however, prevents a direct use in many applications. This paper proposes a novel Differential EMD (DEMD) algorithm based on the sensitivity analysis of the simplex method and offers a speedup at orders of magnitude compared with its brute-force counterparts. The DEMD algorithm is discussed and empirically verified in the visual tracking context. The deformations of the distributions for objects at different time instances are accommodated well by the EMD, and the differential algorithm makes the use of EMD in real-time tracking possible. To further reduce the computation, signatures, i.e., variable-size descriptions of distributions, are employed as an object representation. The new algorithm models and estimates local background scenes as well as foreground objects to handle scale changes in a principled way. Extensive quantitative evaluation of the proposed algorithm has been carried out using benchmark sequences and the improvement over the standard Mean Shift tracker is demonstrated.

INDEX TERMS

Earth mover's distance (EMD), gradient descent, real-time tracking.

CITATION

Qi Zhao, Zhi Yang, Hai Tao, "Differential Earth Mover's Distance with Its Applications to Visual Tracking",

*IEEE Transactions on Pattern Analysis & Machine Intelligence*, vol.32, no. 2, pp. 274-287, February 2010, doi:10.1109/TPAMI.2008.299REFERENCES

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