Range Image Analysis Via Quadtree And Pyramid Structure Based On Surface Curvature

Abstract

This paper presents a method which can expedite, while maintaining the accuracy, range image analysis such as range image segmentation, classification, and location of the region of interest in the range image, thereby making 3-D vision techniques based on range images more useful in manipulating robots accurately in real time. The proposed method incorporates quadtree and pyramid structure in order to quickly analyze range images. In order to make range image analysis independent of the viewing directions, surface curvatures, which are visible-invariant surface characteristics, are exploited. Specifically, we will discuss the following topics: (1) problems of using the surface curvatures for the range image analysis in the presence of noise; (2) generation of the range image pyramid; (3) reliable range image segmentation and classification via split-and-merge using the planarity test and the surface curvatures; (4) incorporation of the quadtree and the pyramid structure to speed up the projection process.