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Algorithms 2018, 11(8), 122; https://doi.org/10.3390/a11080122

Efficient Model-Based Object Pose Estimation Based on Multi-Template Tracking and PnP Algorithms

1
Department of Electrical and Computer Engineering, Tamkang University, 151 Ying-chuan Road, Danshui District, New Taipei City 251, Taiwan
2
Department of Electronic Engineering, Universiti Tunku Abdul Rahman, Jalan Universiti, Bandar Barat, 31900 Kampar, Perak, Malaysia
*
Author to whom correspondence should be addressed.
Received: 5 July 2018 / Revised: 6 August 2018 / Accepted: 10 August 2018 / Published: 12 August 2018
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Abstract

Three-Dimensional (3D) object pose estimation plays a crucial role in computer vision because it is an essential function in many practical applications. In this paper, we propose a real-time model-based object pose estimation algorithm, which integrates template matching and Perspective-n-Point (PnP) pose estimation methods to deal with this issue efficiently. The proposed method firstly extracts and matches keypoints of the scene image and the object reference image. Based on the matched keypoints, a two-dimensional (2D) planar transformation between the reference image and the detected object can be formulated by a homography matrix, which can initialize a template tracking algorithm efficiently. Based on the template tracking result, the correspondence between image features and control points of the Computer-Aided Design (CAD) model of the object can be determined efficiently, thus leading to a fast 3D pose tracking result. Finally, the 3D pose of the object with respect to the camera is estimated by a PnP solver based on the tracked 2D-3D correspondences, which improves the accuracy of the pose estimation. Experimental results show that the proposed method not only achieves real-time performance in tracking multiple objects, but also provides accurate pose estimation results. These advantages make the proposed method suitable for many practical applications, such as augmented reality. View Full-Text
Keywords: model-based pose estimation; 3D pose estimation; homography decomposition; PnP problem; template tracking model-based pose estimation; 3D pose estimation; homography decomposition; PnP problem; template tracking
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Tsai, C.-Y.; Hsu, K.-J.; Nisar, H. Efficient Model-Based Object Pose Estimation Based on Multi-Template Tracking and PnP Algorithms. Algorithms 2018, 11, 122.

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