Abstract
A novel approach for vehicle and pedestrian detection based on data fusion techniques is presented. The work fuses information from a 2D laser scanner and a computer camera, to provide detection and classification of vehicles and pedestrians in road environments. Thanks to the data fusion approach, the limitations of each sensor are overcome. Thus reliable system is provided, fulfilling the demands of road safety applications. Classification is performed using each sensor independently. Laser scanner approach is based in pattern matching and vision approach is based in the classical Histogram of Oriented Gradients features approach. A higher stage performs data fusion using Kalman Filter and Global Nearest Neighbors.
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Acknowledgments
This work was supported by the Spanish Government through the Cicyt projects (GRANT TRA2010-20225-C03-01) and (GRANT TRA 2011-29454-C03-02). CAM through SEGAUTO-II (S2009/DPI-1509).
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García, F., de la Escalera, A., Armingol, J.M. (2014). Novel Method for Vehicle and Pedestrian Detection Based on Information Fusion. In: González Alonso, I. (eds) International Technology Robotics Applications. Intelligent Systems, Control and Automation: Science and Engineering, vol 70. Springer, Cham. https://doi.org/10.1007/978-3-319-02332-8_8
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DOI: https://doi.org/10.1007/978-3-319-02332-8_8
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