Real-Time Calibration and Registration Method for Indoor Scene with Joint Depth and Color Camera.

Zhang, F., Lei, T., Li, J., Cai, X., Shao, X., Chang, J. and Tian, F., 2018. Real-Time Calibration and Registration Method for Indoor Scene with Joint Depth and Color Camera. International Journal of Pattern Recognition and Artificial Intelligence, 32 (7), pp. 1-26.

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DOI: 10.1142/S0218001418540216

Abstract

Traditional vision registration technologies require the design of precise markers or rich texture information captured from the video scenes, and the vision-based methods have high computational complexity while the hardware-based registration technologies lack accuracy. Therefore, in this paper, we propose a novel registration method that takes advantages of RGB-D camera to obtain the depth information in real-time, and a binocular system using the Time of Flight (ToF) camera and a commercial color camera is constructed to realize the three-dimensional registration technique. First, we calibrate the binocular system to get their position relationships. The systematic errors are fitted and corrected by the method of B-spline curve. In order to reduce the anomaly and random noise, an elimination algorithm and an improved bilateral filtering algorithm are proposed to optimize the depth map. For the real-time requirement of the system, it is further accelerated by parallel computing with CUDA. Then, the Camshift-based tracking algorithm is applied to capture the real object registered in the video stream. In addition, the position and orientation of the object are tracked according to the correspondence between the color image and the 3D data. Finally, some experiments are implemented and compared using our binocular system. Experimental results are shown to demonstrate the feasibility and effectiveness of our method.

Item Type:Article
ISSN:0218-0014
Uncontrolled Keywords:Binocular stereoscopic vision; image tracking; depth map; filtering; registration; calibration
Group:Faculty of Media & Communication
ID Code:30289
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:31 Jan 2018 14:49
Last Modified:31 Jan 2018 14:49

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