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3D Depth Cameras in Vision: Benefits and Limitations of the Hardware Read chapter Read first chapter

2014 | OriginalPaper | Chapter

3. Calibration Between Depth and Color Sensors for Commodity Depth Cameras

Authors : Cha Zhang, Zhengyou Zhang

Published in: Computer Vision and Machine Learning with RGB-D Sensors

Publisher: Springer International Publishing

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Abstract

Commodity depth cameras have created many interesting new applications in the research community recently. These applications often require the calibration information between the color and the depth cameras. Traditional checkerboard-based calibration schemes fail to work well for the depth camera, since its corner features cannot be reliably detected in the depth image. In this chapter, we present a maximum likelihood solution for the joint depth and color calibration based on two principles. First, in the depth image, points on the checkerboard shall be coplanar, and the plane is known from color camera calibration. Second, additional point correspondences between the depth and color images may be manually specified or automatically established to help improve calibration accuracy. Uncertainty in depth values has been taken into account systematically. The proposed algorithm is reliable and accurate, as demonstrated by extensive experimental results on simulated and real-world examples.

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previous chapter A State of the Art Report on Multiple RGB-D Sensor Research and on Publicly Available RGB-D Datasets
next chapter Depth Map Denoising via CDT-Based Joint Bilateral Filter
Footnotes
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Metadata
Title
Calibration Between Depth and Color Sensors for Commodity Depth Cameras
Authors
Cha Zhang
Zhengyou Zhang
Copyright Year
2014
Book
Computer Vision and Machine Learning with RGB-D Sensors

Print ISBN: 978-3-319-08650-7

Electronic ISBN: 978-3-319-08651-4

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-319-08651-4_3

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