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Q-MAT: Computing Medial Axis Transform By Quadratic Error Minimization
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DOI：10.1145/2753755.png)
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Abstract
En 中文
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 piece wise linear approximation of the MAT. The method is thoroughly validated and compared with existing methods for MAT computation.
Keywords:
Performance
Design
Medial axis
simplification
quadratic error metric
stability ratio
volume approximation
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