B-SHOT: a binary 3D feature descriptor for fast Keypoint matching on 3D point clouds

TLDR: A comprehensive evaluation on standard benchmarks reveals that B-SHOT offers comparable keypoint matching performance to that of the state-of-the-art real valued 3D feature descriptors, albeit at dramatically lower computational and memory costs.

Abstract: We present the first attempt in creating a binary 3D feature descriptor for fast and efficient keypoint matching on 3D point clouds. Specifically, we propose a binarization technique and apply it on the state-of-the-art 3D feature descriptor, SHOT (Salti et al., Comput Vision Image Underst 125:251–264, 2014) to create the first binary 3D feature descriptor, which we call B-SHOT. B-SHOT requires 32 times lesser memory for its representation while being six times faster in feature descriptor matching, when compared to the SHOT feature descriptor. Next, we propose a robust evaluation metric, specifically for 3D feature descriptors. A comprehensive evaluation on standard benchmarks reveals that B-SHOT offers comparable keypoint matching performance to that of the state-of-the-art real valued 3D feature descriptors, albeit at dramatically lower computational and memory costs.