Compression of surface registrations using Beltrami coefficients

Surface registration is widely used in machine vision and medical imaging, where 1-1 correspondences between surfaces are computed to study their variations. Surface maps are usually stored as the 3D coordinates each vertex is mapped to, which often requires lots of storage memory. This causes inconvenience in data transmission and data storage, especially when a large set of surfaces are analyzed. To tackle this problem, we propose a novel representation of surface diffeomorphisms using Beltrami coefficients, which are complex-valued functions defined on sur

• Type: Journal
• Year: 2010
• Where: CVPR
• Authors: Lok Ming Lui, Tsz Wai Wong, Paul M. Thompson, Tony F. Chan, Xianfeng Gu, Shing-Tung Yau
• Keywords: Computer Vision, CVPR 2010, Storage Memory, Surface Maps, Surface Registration