Robust non-parametric data fitting for correspondence modeling

• Main Authors: LIN, Wen-yan, CHENG, Ming-Ming, ZHENG, Shuai, LU, Jiangbo, CROOK, Nigel
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2013
• Subjects: curve fitting; matching; non-parametric; spline; warping; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/4809; https://ink.library.smu.edu.sg/context/sis_research/article/5812/viewcontent/DataFittingICCV13.pdf
• Institution: Singapore Management University

We propose a generic method for obtaining nonparametric image warps from noisy point correspondences. Our formulation integrates a huber function into a motion coherence framework. This makes our fitting function especially robust to piecewise correspondence noise (where an image section is consiste...