基于视平面上特征计算的视点选择

Viewpoint Selection by Feature Measurement on the Viewing Plane

提出一种能高效观察三维模型的视点选择方法.该方法基于视平面定义一种曲率特征,以度量模型的三维几何特征在视平面上的分布和体现状况,并由此计算与视点相关的一种熵值;然后对各个视点相关的这种熵值进行比较,可得到熵值最大的视点.实验结果表明,采用该方法找到的视点能观察到模型尽可能多的显著特征,与人眼的观察习惯比较接近.与已有方法相比,文中方法计算简单、不需要语义计算、有较高的工作效率.

This paper presents a new method for selecting good viewpoints to efficiently observe an object. It defines a view-dependent curvature to measure the distribution and appearance of the geometric features on the viewing plane, and based on the curvature, it computes an entropy value for every candidate viewpoint. Afterwards, the viewpoints with the maximal entropy values are selected as the good viewpoints. The results of experiments show that the viewpoints selected by the new method could have salient features visible as much as possible, very likely to achieve what is required bypeople to view an object. In comparison with existing methods, the new method is simple, without semantic computation, and works very well.