Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The medial axis transform has long been known as an intrinsic shape representation supporting a variety of shape analysis and synthesis tasks. Hover, for a given shape, it is hard to obtain its faithful, concise and stable medial axis, which hinders the application of the medial axis. ,  introduce the  medial mesh , a new discrete representation of the medial axis. A medial mesh is a 2D simplicial complex coupled with a radius function that provides a piecewise linear approximation to the medial axis.  further present an effective algorithm for computing a concise and stable medial mesh for a given shape. Our algorithm is quantitatively driven by a shape approximation error metric, and progressively simplifies an initial medial mesh by iteratively contracting edges until the approximation error reaches a predefined threshold.  further demonstrate the superior efficiency and accuracy of our method over existing methods for medial axis simplification.
['Feng Sun', 'Yi-King Choi', 'Yizhou Yu', 'Wenping Wang']
I am writing a research paper on a idea Medial Meshes – A Compact and Accurate Representation of Medial Axis Transform
[{"from": "human", "value": "I am writing a research paper on a idea Medial Meshes \u2013 A Compact and Accurate Representation of Medial Axis Transform"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The medial axis transform has long been known as an intrinsic shape representation supporting a variety of shape analysis and synthesis tasks. Hover, for a given shape, it is hard to obtain its faithful, concise and stable medial axis, which hinders the application of the medial axis. ,  introduce the  medial mesh , a new discrete representation of the medial axis. A medial mesh is a 2D simplicial complex coupled with a radius function that provides a piecewise linear approximation to the medial axis.  further present an effective algorithm for computing a concise and stable medial mesh for a given shape. Our algorithm is quantitatively driven by a shape approximation error metric, and progressively simplifies an initial medial mesh by iteratively contracting edges until the approximation error reaches a predefined threshold.  further demonstrate the superior efficiency and accuracy of our method over existing methods for medial axis simplification."}]