Object detection using a combination of multiple 3D feature descriptors

Abstract

This paper presents an approach for object pose estimation using a combination of multiple feature descriptors. We propose to use a combination of three feature descriptors, capturing both surface and edge information. Those descriptors individually perform well for different object classes. We use scenes from an established RGB-D dataset and our own recorded scenes to justify the claim that by combining multiple features, we in general achieve better performance. We present quantitative results for descriptor matching and object detection for both datasets.