Abstract
In autonomous driving, the ability to correctly detect and calculate the distance to objects is a fundamental task of the perception system. The objective of this paper is to present a robust object detection system using a Time of Flight (ToF) camera. The system is designed for covering the blind spot areas of vehicles and to be integrated with an autonomous vehicle perception system. ToF cameras generate images with depth information in real time as well as providing grayscale images. The accuracy of the measurements obtained depends greatly on the correct calibration of the camera, therefore in this paper, a calibration process for the Sentis 3D-M420 ToF camera is presented. For the object detection system that has been developed, different descriptors and classifiers have been analyzed. To evaluate the system tests were performed in real situations using a series of images obtained with the Sentis 3D-M420 camera during autonomous driving tests.
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Acknowledgements
This work was partially supported by ViSelTR (ref. TIN2012-39279), DGT (ref. SPIP2017-02286) and UPCA13-2E-1929 Spanish Government projects, and the “Research Programme for Groups of Scientific Excellence in the Region of Murcia” of the Seneca Foundation (Agency for Science and Technology in the Region of Murcia-19895/GERM/15).
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Miller, L., García, A.R., Lorente, P.J.N., Andrés, C.F., Morón, R.B. (2020). Time of Flight Camera Calibration and Obstacle Detection Application for an Autonomous Vehicle. In: Świątek, J., Borzemski, L., Wilimowska, Z. (eds) Information Systems Architecture and Technology: Proceedings of 40th Anniversary International Conference on Information Systems Architecture and Technology – ISAT 2019. ISAT 2019. Advances in Intelligent Systems and Computing, vol 1051. Springer, Cham. https://doi.org/10.1007/978-3-030-30604-5_25
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DOI: https://doi.org/10.1007/978-3-030-30604-5_25
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