Abstract

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. This work was supported by the Spanish Government through the CICYTprojects (TRA2013-48314-C3-1-R and TRA2015-63708-R) and Comunidad de Madrid through SEGVAUTO-TRIES (S2013/MIT-2713). Publicado

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The different versions of the original document can be found in:

https://doi.org/10.3390/s16091492 under the license cc-by
https://doaj.org/toc/1424-8220 under the license http://creativecommons.org/licenses/by-nc-nd/3.0/es/
http://dx.doi.org/10.3390/s16091492
https://www.mdpi.com/1424-8220/16/9/1492,
https://www.mdpi.com/1424-8220/16/9/1492/pdf,
http://europepmc.org/abstract/MED/27649178,
https://doi.org/10.3390/s16091492,
https://trid.trb.org/view/1424454,
https://core.ac.uk/display/90759678,
https://academic.microsoft.com/#/detail/2520143344 under the license https://creativecommons.org/licenses/by/4.0/
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Published on 01/01/2016

Volume 2016, 2016
DOI: 10.3390/s16091492
Licence: Other

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