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Sensors 2016, 16(9), 1492;

Pose Self-Calibration of Stereo Vision Systems for Autonomous Vehicle Applications

Intelligent Systems Laboratory, Universidad Carlos III de Madrid/Avda de la Universidad 30, Leganés, Madrid 28911, Spain
Author to whom correspondence should be addressed.
Academic Editor: Felipe Jimenez
Received: 10 June 2016 / Revised: 8 August 2016 / Accepted: 7 September 2016 / Published: 14 September 2016
(This article belongs to the Special Issue Sensors for Autonomous Road Vehicles)
PDF [3931 KB, uploaded 14 September 2016]


Nowadays, intelligent systems applied to vehicles have grown very rapidly; their goal is not only the improvement of safety, but also making autonomous driving possible. Many of these intelligent systems are based on making use of computer vision in order to know the environment and act accordingly. It is of great importance to be able to estimate the pose of the vision system because the measurement matching between the perception system (pixels) and the vehicle environment (meters) depends on the relative position between the perception system and the environment. A new method of camera pose estimation for stereo systems is presented in this paper, whose main contribution regarding the state of the art on the subject is the estimation of the pitch angle without being affected by the roll angle. The validation of the self-calibration method is accomplished by comparing it with relevant methods of camera pose estimation, where a synthetic sequence is used in order to measure the continuous error with a ground truth. This validation is enriched by the experimental results of the method in real traffic environments. View Full-Text
Keywords: camera pose estimation; stereo vision; advanced driver assistance systems; intelligent vehicles camera pose estimation; stereo vision; advanced driver assistance systems; intelligent vehicles

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Musleh, B.; Martín, D.; Armingol, J.M.; De la Escalera, A. Pose Self-Calibration of Stereo Vision Systems for Autonomous Vehicle Applications. Sensors 2016, 16, 1492.

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