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J. Imaging 2016, 2(1), 5; doi:10.3390/jimaging2010005

Glidar: An OpenGL-based, Real-Time, and Open Source 3D Sensor Simulator for Testing Computer Vision Algorithms

West Virginia University, 395 Evansdale Drive, Morgantown, WV 26506, USA
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Academic Editor: Gonzalo Pajares Martinsanz
Received: 27 October 2015 / Revised: 19 January 2016 / Accepted: 20 January 2016 / Published: 29 January 2016
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Abstract

3D sensors such as lidars, stereo cameras, time-of-flight cameras, and the Microsoft Kinect are increasingly found in a wide range of applications, including gaming, personal robotics, and space exploration. In some cases, pattern recognition algorithms for processing depth images can be tested using actual sensors observing real-world objects. In many situations, however, it is common to test new algorithms using computer-generated synthetic images, as such simulations tend to be faster, more flexible, and less expensive than hardware tests. Computer generation of images is especially useful for Monte Carlo-type analyses or for situations where obtaining real sensor data for preliminary testing is difficult (e.g., space applications). We present Glidar, an OpenGL and GL Shading Language-based sensor simulator, capable of imaging nearly any static three-dimensional model. Glidar allows basic object manipulations, or may be connected to a physics simulator for more advanced behaviors. It permits publishing to a tcp socket at high frame-rates or can save to pcd (point cloud data) files. The software is written in C++, and is released under the open source bsd license. View Full-Text
Keywords: 3D sensors; sensor simulators 3D sensors; sensor simulators
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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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MDPI and ACS Style

Woods, J.O.; Christian, J.A. Glidar: An OpenGL-based, Real-Time, and Open Source 3D Sensor Simulator for Testing Computer Vision Algorithms. J. Imaging 2016, 2, 5.

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