Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/138260
Title: Multiple consumer-grade depth camera registration using everyday objects
Authors: Deng, Teng
Cai, Jianfei
Cham, Tat-Jen
Zheng, Jianmin
Keywords: Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Issue Date: 2017
Source: Deng, T., Cai, J., Cham, T.-J., & Zheng, J. (2017). Multiple consumer-grade depth camera registration using everyday objects. Image and Vision Computing, 62, 1-7. doi:10.1016/j.imavis.2017.03.005
Journal: Image and Vision Computing
Abstract: The registration of multiple consumer-grade depth sensors is a challenging task due to noisy and systematic distortions in depth measurements. Most of the existing works heavily rely on large number of checkerboard observations for calibration and registration of multiple depth cameras, which is tedious and not flexible. In this paper, we propose a more practical method for conducting and maintaining registration of multi-depth sensors, via replacing checkerboards with everyday objects found in the scene, such as regular furniture. Particularly, high quality pre-scanned 3D shapes of standard furniture are used as calibration targets. We propose a unified framework that jointly computes the optimal extrinsic calibration and depth correction parameters. Experimental results show that our proposed method significantly outperforms state-of-the-art depth camera registration methods.
URI: https://hdl.handle.net/10356/138260
ISSN: 0262-8856
DOI: 10.1016/j.imavis.2017.03.005
Rights: © 2017 Elsevier B.V. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:IMI Journal Articles

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