Abstract
The driver’s loss of attention is an important problem in which are spent considerable research efforts in different areas such as psychology, automobile technology, computer vision and driving assistance. We use here a simple algorithm based on rigid-body and motion detection. This scheme efficiently segments moving objects using the visual field of the driver’s rear-view mirror. The overtaking scene in the rear-view mirror is distorted due to perspective, making it difficult to detect the overtaking car. Thus we propose two alternative methods to deal with this problem and compare the results in different overtaking sequences.
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.
References
Reichardt, W.: Autocorrelation, a principle for the evaluation of sensory information by central nervous system. In: Rosenblith, W.A. (ed.) Sensory Communication, pp. 303–317 (1961)
Hubel, D., Wiesel, T.: Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. Journal of Physiology (London) 160, 106–154 (1962)
Petkov, N., Kruizinga, P.: Computational models of visual neurons specialized in the detection of periodic and a periodic oriented visual stimuli: Bar and grating cells. Biological Cybernetics 76(2), 83–96 (1997)
Dresp, B., Grossberg, S.: Contour integration across polarities and spatial gaps: From local contrast to global grouping. Vision Research 37, 913–924 (1997)
Marr, D.: Vision. W. H. Freeman and Company, New York (1982)
Gonzalez, R., Woods, R.: Digital Image Processing. Addison-Wesley, London (1992)
Mota, S., Ros, E., Ortigosa, E.M., Pelayo, F.J.: Bio-Inspired Motion Detection for Blind Spot Overtaking Monitor. International Journal of Robotics and Automation 19(4), 190–196 (2004)
Mota, S., Ros, E., Díaz, J., Ortigosa, E.M., Prieto, A.: Motion-driven segmentation by competitive neural processing. Neural Processing Letters 22(2), 125–177 (2005)
Mota, S., Ros, E., Díaz, J., Agis, R., de Toro, F.: Bio-inspired motion-based object segmentation. In: Campilho, A., Kamel, M. (eds.) ICIAR 2006. LNCS, vol. 4141, pp. 196–205. Springer, Heidelberg (2006)
Mallot, H.A., Bulthoff, H.H., Little, J.J., Bohrer, S.: Inverse perspective mapping simplifies optical flow computation and obstacle detection. Biol. Cybern. 64, 177–185 (1991)
Tan, S., Dale, J., Johnston, A.: Effects of Inverse Perspective Mapping on Optic Flow. In: ECOVISION Workshop, Isle of Skye, Scotland (2004)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Mota, S., Ros, E., Díaz, J., Agís, R., Rodriguez, R., Carrillo, R. (2007). Dealing with the Perspective Distortion to Detect Overtaking Cars for Driving Assistance. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2007. Lecture Notes in Computer Science, vol 4477. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72847-4_19
Download citation
DOI: https://doi.org/10.1007/978-3-540-72847-4_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72846-7
Online ISBN: 978-3-540-72847-4
eBook Packages: Computer ScienceComputer Science (R0)