Affiliation:
1. Tsinghua University
2. The Pennsylvania State University
3. University of Texas at Dallas
4. Shandong University
5. University of Hong Kong
Abstract
The medial axis transform (MAT) is an important shape representation for shape approximation, shape recognition, and shape retrieval. Despite years of research, there is still a lack of effective methods for efficient, robust and accurate computation of the MAT. We present an efficient method, called
Q-MAT
, that uses quadratic error minimization to compute a structurally simple, geometrically accurate, and compact representation of the MAT. We introduce a new error metric for approximation and a new quantitative characterization of unstable branches of the MAT, and integrate them in an extension of the well-known quadric error metric (QEM) framework for mesh decimation. Q-MAT is fast, removes insignificant unstable branches effectively, and produces a simple and accurate piecewise linear approximation of the MAT. The method is thoroughly validated and compared with existing methods for MAT computation.
Funder
National Basic Research Program of China
National Science Foundation of China
Research Grant Council of Hong Kong
Cancer Prevention & Research Institute of Texas
National Science Foundation
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Graphics and Computer-Aided Design
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