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.
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Schedule a callMore From: The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)
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