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Robust Intrinsic and Extrinsic Calibration of RGB-D Cameras | Filippo Basso
; Emanuele Menegatti
; Alberto Pretto
; | Date: |
20 Jan 2017 | Abstract: | Color-depth cameras (RGB-D cameras) have become the primary sensors in most
robotics systems, from service robotics to industrial robotics applications.
Typical consumer-grade RGB-D cameras are provided with a coarse intrinsic and
extrinsic calibration that generally does not meet the accuracy requirements
needed by many robotics applications (e.g., high accuracy 3D environment
reconstruction and mapping, high precision object recognition and localization,
...). In this paper, we propose a human-friendly, reliable and accurate
calibration framework that enables to easily estimate both the intrinsic and
extrinsic parameters of a general color-depth sensor couple. Our approach is
based on a novel, two components, measurement error model that unifies the
error sources of different RGB-D pairs based on different technologies, such as
structured-light 3D cameras and time-of-flight cameras. The proposed correction
model is implemented using two different parametric undistortion maps that
provide the calibrated readings by means of linear combinations of control
functions. Our method provides some important advantages compared to other
state-of-the-art systems: it is general (i.e., well suited for different types
of sensors), it is based on an easy and stable calibration protocol, it
provides a greater calibration accuracy, and it has been implemented within the
ROS robotics framework. We report detailed and comprehensive experimental
validations and performance comparisons to support our statements. | Source: | arXiv, 1701.5748 | Services: | Forum | Review | PDF | Favorites |
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