3D Binary Signatures

TL;DR

This paper introduces a fast binary descriptor for 3D point clouds called 3D Binary Signature (3DBS), which enables efficient keypoint matching using Hamming distance and outperforms existing descriptors.

Contribution

The paper presents a novel 3D binary descriptor that improves matching speed and accuracy for 3D point cloud keypoints compared to prior methods.

Findings

3DBS achieves faster matching times.

3DBS outperforms state-of-the-art descriptors on evaluation metrics.

The method effectively describes 3D keypoints with binary vectors.

Abstract

In this paper, we propose a novel binary descriptor for 3D point clouds. The proposed descriptor termed as 3D Binary Signature (3DBS) is motivated from the matching efficiency of the binary descriptors for 2D images. 3DBS describes keypoints from point clouds with a binary vector resulting in extremely fast matching. The method uses keypoints from standard keypoint detectors. The descriptor is built by constructing a Local Reference Frame and aligning a local surface patch accordingly. The local surface patch constitutes of identifying nearest neighbours based upon an angular constraint among them. The points are ordered with respect to the distance from the keypoints. The normals of the ordered pairs of these keypoints are projected on the axes and the relative magnitude is used to assign a binary digit. The vector thus constituted is used as a signature for representing the keypoints. The matching is done by using hamming distance. We show that 3DBS outperforms state of the art descriptors on various evaluation metrics.