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Marker-Less 3d Object Recognition and 6d Pose Estimation for Homogeneous Textureless Objects: An RGB-D Approach

Multimedia Research Centre, Department of Computing Science, University of Alberta, Edmonton, AB T6G 2R3, Canada
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Sensors 2020, 20(18), 5098; https://doi.org/10.3390/s20185098
Received: 25 June 2020 / Revised: 24 August 2020 / Accepted: 2 September 2020 / Published: 7 September 2020
(This article belongs to the Section Physical Sensors)
The task of recognising an object and estimating its 6d pose in a scene has received considerable attention in recent years. The accessibility and low-cost of consumer RGB-D cameras, make object recognition and pose estimation feasible even for small industrial businesses. An example is the industrial assembly line, where a robotic arm should pick a small, textureless and mostly homogeneous object and place it in a designated location. Despite all the recent advancements of object recognition and pose estimation techniques in natural scenes, the problem remains challenging for industrial parts. In this paper, we present a framework to simultaneously recognise the object’s class and estimate its 6d pose from RGB-D data. The proposed model adapts a global approach, where an object and the Region of Interest (ROI) are first recognised from RGB images. The object’s pose is then estimated from the corresponding depth information. We train various classifiers based on extracted Histogram of Oriented Gradient (HOG) features to detect and recognize the objects. We then perform template matching on the point cloud based on surface normal and Fast Point Feature Histograms (FPFH) to estimate the pose of the object. Experimental results show that our system is quite efficient, accurate and robust to illumination and background changes, even for the challenging objects of Tless dataset. View Full-Text
Keywords: 6d pose estimation; 3d object recognition; textureless objects; homogeneous objects 6d pose estimation; 3d object recognition; textureless objects; homogeneous objects
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MDPI and ACS Style

Hajari, N.; Lugo Bustillo, G.; Sharma, H.; Cheng, I. Marker-Less 3d Object Recognition and 6d Pose Estimation for Homogeneous Textureless Objects: An RGB-D Approach. Sensors 2020, 20, 5098. https://doi.org/10.3390/s20185098

AMA Style

Hajari N, Lugo Bustillo G, Sharma H, Cheng I. Marker-Less 3d Object Recognition and 6d Pose Estimation for Homogeneous Textureless Objects: An RGB-D Approach. Sensors. 2020; 20(18):5098. https://doi.org/10.3390/s20185098

Chicago/Turabian Style

Hajari, Nasim, Gabriel Lugo Bustillo, Harsh Sharma, and Irene Cheng. 2020. "Marker-Less 3d Object Recognition and 6d Pose Estimation for Homogeneous Textureless Objects: An RGB-D Approach" Sensors 20, no. 18: 5098. https://doi.org/10.3390/s20185098

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