3D ORTHOGRAPHIC RECONSTRUCTION BASED ON ROBUST FACTORIZATION METHOD WITH OUTLIERS (TP-P1)

Author(s) : Li Xi (Institute of Artificial Intelligence and Robotics, XiĄŻan Jiaotong University, XiĄŻan, Shaanxi Province 710049, PR China, China)

Abstract : It is well known that both shape and motion can be factorized directly from the measurement matrix constructed from feature points trajectories under orthographic camera model. In practical applications, the measurement matrix might be contaminated by noises and contains outliers and missing values. A direct SVD(Singular Value Decomposition) to the measurement matrix with outliers would yield erroneous result. The main contribution of this paper is that it presents a new algorithm for computing SVD by linear l1-norm regression. It is robust to outliers and can handle missing data naturally. The linear regression problem is solved using weighted-median algorithm and is simple to implement. The proposed robust factorization method with outliers can improve the reconstruction result remarkably. Quantitative and qualitative experiments illustrate the good performance of our approach.

Menu