3D part segmentation using simulated electrical charge distributions

被引:62
作者
Wu, KN [1 ]
Levine, MD [1 ]
机构
[1] MCGILL UNIV, CTR INTELLIGENT MACHINES, MONTREAL, PQ H3A 2A7, CANADA
基金
加拿大自然科学与工程研究理事会;
关键词
computer vision; 3D; range data; shape; part segmentation; physics-based vision; electrical charge density distribution; finite element; surface triangulation; surface characterization;
D O I
10.1109/34.632982
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A novel approach to 3D part segmentation is presented. It is a well-known physical fact that electrical charge on the surface of a conductor tends to accumulate at a sharp convexity and vanish at a sharp concavity. Thus, object part boundaries, which are usually denoted by a sharp surface concavity, can be detected by simulating the electrical charge density over the object surface and locating surface points which exhibit local charge density minima. Beginning with single-or multi-view range data of a 3D object, we simulate the charge density distribution over an object's surface which has been tessellated by a triangular mesh. We detect the deep surface concavities by tracing local charge density minima and then decompose the object into parts at these points. The charge density computation does not require an assumption on surface smoothness and uses weighted global data to produce robust local surface features for part segmentation.
引用
收藏
页码:1223 / 1235
页数:13
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