Abstract
This paper describes a system for pedestrian detection in infrared images implemented and tested on an experimental vehicle. A specific stabilization procedure is applied after image acquisition and before processing to cope with vehicle movements affecting the camera calibration. The localization of pedestrians is based on the search for warm symmetrical objects with specific size and aspect ratio. A set of filters is used to reduce false detections. The final validation process relies on the human shape’s morphological characteristics.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Nanda, H., Davis, L.: Probabilistic Template Based Pedestrian Detection in Infrared Videos. In: Procs. IEEE Intelligent Vehicles Symposium 2002 (June 2002)
Xu, F., Fujimura, K.: Pedestrian Detection and Tracking with Night Vision. In: Procs. IEEE Intelligent Vehicles Symposium (June 2002)
Guilloux, Y.L., Lonnoy, J.: PAROTO Project: The Benefit of Infrared Imagery for Obstacle Avoidance. In: Procs. IEEE Intelligent Vehicles Symposium 2002 (June 2002)
Tsuji, T., Hattori, H., Watanabe, M., Nagaoka, N.: Development of Night-vision System. IEEE Trans. on Intelligent Transportation Systems 3, 203–209 (2002)
Bertozzi, M., Broggi, A., Fascioli, A., Sechi, M.: Shape-based Pedestrian Detection. In: Procs. IEEE Intelligent Vehicles Symposium 2000, October 2000, pp. 215–220 (2000)
Gavrila, D.M., Geibel, J.: Shape-Based Pedestrian Detection and Tracking. In: Procs. IEEE Intelligent Vehicles Symposium 2002 (June 2002)
Curio, C., Edelbrunner, J., Kalinke, T., Tzomakas, C., von Seelen, W.: Walking Pedestrian Recognition. IEEE Trans. on ITS 1, 155–163 (2000)
Oren, M., Papageorgiu, C., Sihna, P., Osuna, E., Poggio, T.: Pedestrian Detection using Wavelet Templates. In: Procs. IEEE Conf. on Computer Vision and Pattern Recognition, San Juan, Puerto Rico, pp. 193–199 (1997)
Zhao, L., Thorpe, C.: Stereo- and Neural Network-based Pedestrian Detection. In: Procs. IEEE Intl. Conf. on Intelligent Transportation Systems 1999, pp. 298–303 (October 1999)
Heisele, B., Wöhler, C.: Motion-based Recognition of Pedestrians. In: Procs. IEEE Intl Conf. on Pattern Recognition, pp. 1325–1330 (June 1998)
Cutler, R., Davis, L.S.: Robust real-time periodic motion detection, analysis and applications. IEEE Trans. on PAMI 22, 781–796 (2000)
Bertozzi, M., Broggi, A., Graf, T., Grisleri, P., Meinecke, M.: Pedestrian Detection in Infrared Images. In: Procs. IEEE Intelligent Vehicles Symposium 2003 (June 2003) (in press)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bertozzi, M. et al. (2003). IR Pedestrian Detection for Advanced Driver Assistance Systems. In: Michaelis, B., Krell, G. (eds) Pattern Recognition. DAGM 2003. Lecture Notes in Computer Science, vol 2781. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45243-0_74
Download citation
DOI: https://doi.org/10.1007/978-3-540-45243-0_74
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40861-1
Online ISBN: 978-3-540-45243-0
eBook Packages: Springer Book Archive