IVVI 2.0: An intelligent vehicle based on computational perception

•The stereo vision system for obstacle and free space detection is explained.•The far infrared pedestrian detection system is fostered in urban environments.•The driver safety system through facial recognition is analyzed in detail.•Our obstacle detection and classification system based on data fusi...

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Veröffentlicht in:Expert systems with applications 2014-12, Vol.41 (17), p.7927-7944
Hauptverfasser: Martín, D., García, F., Musleh, B., Olmeda, D., Peláez, G., Marín, P., Ponz, A., Rodríguez, C., Al-Kaff, A., de la Escalera, A., Armingol, J.M.
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Sprache:eng
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Zusammenfassung:•The stereo vision system for obstacle and free space detection is explained.•The far infrared pedestrian detection system is fostered in urban environments.•The driver safety system through facial recognition is analyzed in detail.•Our obstacle detection and classification system based on data fusion is presented.•We explain the vehicle positioning using visual odometry or GNSS–IMU fusion. This paper presents the IVVI 2.0 a smart research platform to foster intelligent systems in vehicles. Computational perception in intelligent transportation systems applications has advantages, such as huge data from vehicle environment, among others, so computer vision systems and laser scanners are the main devices that accomplish this task. Both have been integrated in our intelligent vehicle to develop cutting-edge applications to cope with perception difficulties, data processing algorithms, expert knowledge, and decision-making. The long-term in-vehicle applications, that are presented in this paper, outperform the most significant and fundamental technical limitations, such as, robustness in the face of changing environmental conditions. Our intelligent vehicle operates outdoors with pedestrians and others vehicles, and outperforms illumination variation, i.e.: shadows, low lighting conditions, night vision, among others. So, our applications ensure the suitable robustness and safety in case of a large variety of lighting conditions and complex perception tasks. Some of these complex tasks are overcome by the improvement of other devices, such as, inertial measurement units or differential global positioning systems, or perception architectures that accomplish sensor fusion processes in an efficient and safe manner. Both extra devices and architectures enhance the accuracy of computational perception and outreach the properties of each device separately.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2014.07.002