In this paper, we propose a novel local image descriptor DoP which is termed as the difference of im- ages represented by polynomials in different degrees. Once an interest point/region is extracted by a common image detector such as Harris corner, our DoP descriptor is able to characterize the interest point/region with high distinc- tiveness, compactness, and robustness to viewpoint change, image blur, and illumination variation. To efficiently build DoP descriptor, we propose to numerically reduce the computational cost by jumping over the repeatedly calculating polynomial representation. Our experimental results demonstrate a better performance compared to several state-of-art candidates.
B. Zheng, Y. Sun, J. Takamatsu, K. Ikeuchi, "A Feature Descriptor by Difference of Polynomials" , IPSJ Trans. on Computer Vision and Applications, 2013.
B. Zheng, Y. Sun, J. Takamatsu, K. Ikeuchi, "A Feature Descriptor by Difference of Polynomials", Meeting on Image Recognition and Understanding (MIRU) 2013, Japan.