Simultaneous 3D Object Recognition and Pose Estimation Based on RGB-D Images

doi:10.1109/ACCESS.2018.2808225

機構典藏 > College of Engineering > Graduate Institute & Department of Electrical Engineering > Journal Article > Item 987654321/115540

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/115540

Title:	Simultaneous 3D Object Recognition and Pose Estimation Based on RGB-D Images
Authors:	Tsai, Chi-Yi;Tsai, Shu-Hsiang
Date:	2018-02-20
Issue Date:	2018-11-08 12:11:12 (UTC+8)
Publisher:	IEEE
Abstract:	Object recognition and pose estimation are essential functions in applications of computer vision, and they also are fundamental modules in robotic vision systems. In recent years, RGB-D cameras become more and more popular, and the 3D object recognition technology has got more and more attention. In this paper, a novel design of simultaneous 3D object recognition and pose estimation algorithm is proposed based on RGB-D images. The proposed system converts the input RGB-D image to colored point cloud data and extracts features of the scene from the colored point cloud. Then, the existing color signature of histograms of orientations (CSHOT) description algorithm is employed to build descriptors of the detected features based on local texture and shape information. Given the extracted feature descriptors, a two-stage matching process is performed to find correspondences between the scene and a colored point cloud model of an object. Next, a Hough voting algorithm is used to filter out matching errors in the correspondence set and estimate the initial 3D pose of the object. Finally, the pose estimation stage employs RANdom SAmple Consensus (RANSAC) and hypothesis verification algorithms to refine the initial pose and filter out poor estimation results with error hypotheses. Experimental results show that the proposed system not only successfully recognizes the object in a complex scene but also accurately estimates the 3D pose information of the object with respect to the camera.
Relation:	IEEE Access 6, p.28859-28869
DOI:	10.1109/ACCESS.2018.2808225
Appears in Collections:	[Graduate Institute & Department of Electrical Engineering] Journal Article

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