3D shape estimation from silhouettes using mean-shift

In this article, a novel method to accurately estimate 3D surface of objects of interest is proposed. Each ray projected from 2D image plane to 3D space is modelled with the Gaussian kernel function. Then a mean shift algorithm with an annealing scheme is used to find maximums of the probability density function and recovers the 3D surface. Experimental results show that our method is more accurate to estimate 3D surface than the Radon transform-based approach.

• Type: Conference
• Year: 2010
• Where: ICASSP
• Authors: Donghoon Kim, Jonathan Ruttle, Rozenn Dahyot
• Keywords: Gaussian Kernel Function, ICASSP 2010, Probability Density Function, Radon Transform-based Approach, Signal Processing