3D Binary Signatures
This addresses the need for fast and effective 3D point cloud matching in applications like robotics and computer vision, representing an incremental improvement by adapting 2D binary descriptor concepts to 3D.
The paper tackles the problem of efficient 3D point cloud matching by proposing a novel binary descriptor called 3D Binary Signature (3DBS), which outperforms state-of-the-art descriptors on various evaluation metrics.
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.