多尺度空间的自动形状模型的构造算法

Automatic Shape Model Construction in Multiscale Space

提出一种基于多尺度的轮廓模型自动构造算法,可归纳出有形变的物体的轮廓结构.对于噪声及形变程度差异较大的轮廓,首先用多尺度的方法将轮廓分段匹配,根据每段曲线上的噪声和形变程度选择合适的滤波尺度;然后对由轮廓匹配得到的曲线段的对应关系进行归纳调整,得到它们的通用结构模型.该算法适用于对一类具有相同结构但局部存在不同程度噪声和形变的闭合轮廓建立模型,将其用在行人轮廓的建模上取得了较好的效果.

This paper presents a novel approach for learning models from deformable shape contours using multi-scale matching. For the contours with a large degree of noise and deformation, firstly, contours are segmented and matched in multi-scale space. In this process, the scale parameter is adjusted according to the noise and deformation degree. Then, shape model is deduced from the correspondence of curve sequences. The proposed approach is effective to deal with noise and deformation of the models of closed contours. An application is reported to build the models of pedestrian contours with good result.