距离图像局部特征提取方法综述

Survey of Local Feature Extraction on Range Images

基于距离图像的三维目标识别是计算机视觉领域的研究热点,而局部特征提取则是实现遮挡和复杂场景下三维目标识别的关键.文中首先介绍距离图像及其表示形式,详细分析法向量、曲率和形状索引等微分几何属性.进而将局部特征检测方法分类为固定尺度和自适应尺度方法,将局部特征描述方法分类为基于深度信息、基于点云空间分布和基于几何属性分布的方法,并对各种具体算法进行阐述、分析和定性评价.最后对现有方法进行归纳总结,并指出所面临的挑战及进一步研究的方向.

Three dimensional （3D） object recognition is a hot research topic in computer vision. Local feature extraction is a key stage for 3D object recognition with the presence of occlusion and clutter. Firstly, range images and their representations are described. The differential geometric attributes are introduced, including the surface normal, the curvature and the shape index. Then, the local feature detection methods are classified into fixed scale method and adaptive scale method. And the local feature description methods are classified into depth value based, point spatial distribution based and geometric attributes distribution based methods. These methods with their merits and demerits are described. Finally, the existing methods are summarized and several challenges and future research directions are pointed out.