Physical Scale Intensity-Based Range Keypoints

This paper presents a method for detecting, describing, and matching keypoints in combined range-intensity data. We extend a 2D image-based detection and description framework to 3D using an image back-projected onto a range scan. A key feature of the framework is a physical scale space for detecting keypoints, which eliminates errors in scale during both detection and matching. We develop smoothing, differentiation, and description techniques that are focused on making the keypoint invariant to viewpoint, sampling, and intensity changes. We demonstrate the power of our algorithm with comparisons to a back-projected SIFT algorithm, showing that it is able to find and match keypoints in a variety of challenging scan pairs.