基于感知的视点自动选取

Perceptual-Based Automatic Viewpoint Selection

为了在三维模型浏览系统中自动选取一个好的视点,使用户能够更有效地获取模型信息,提出一种自动视点选取算法.该算法基于视点信息熵理论和人眼的视觉感知理论,构建出一个与视点相关的模型视觉特征度量函数,并采用类随机梯度下降法来优化求解该目标函数,得到该度量标准下的最佳视点.实验结果证明,与已有算法相比,采用文中算法自动得到的最佳视点更符合人眼对于三维模型形状的心理感知,通过GPU加速,算法速度也大大提高.

By automatically selecting a good viewpoint in the 3D visualization systems,users can acquire information of the 3D models more effectively.Based on the theory of information entropy and human perception,this paper presents an algorithm for automatic viewpoint selection.We design a perceptual feature function of the object with respect to all possible viewpoints.This function is then optimized by using a stochastic gradient descent like method.Experimental results show that our selected viewpoint provides a best view of the object which conforms very well with human perception.By using GPU,its time cost is also greatly reduced.