Abstract
In this paper, we propose a new feature descriptor for 3D object recognition using an RGB-D camera. Our feature descriptor is invariant to a change of viewpoint and consists of a histogram of surface normals of an object around the keypoints and a histogram of color(hue and saturation) information of an object around the keypoints. We call this feature descriptor "HS-SHOT." To show the validity of our method, we conduct experiments where we compare HS-SHOT and state-of-the-art feature descriptors. Through experiments we confirm that the performance of 3D object recognition using HS-SHOT is superior to that of 3D object recognition using state-of-the-art feature descriptors.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.