Stereovision-based object segmentation for automotive applications

Eurasip Journal on Applied Signal Processing

Volumn 2005, Issue 14, 2005, Pages 2322-2329

  Huang, Yingping ^a   Fu, Shan ^b   Thompson, Chris ^b,c  

^a UNIVERSITY OF WARWICK   (United Kingdom)

^b CRANFIELD UNIVERSITY   (United Kingdom)

^c Department of Applied Computation ^*  (United Kingdom)

Author keywords

Objects detection; Segmentation; Stereovision

Indexed keywords

OBJECTS DETECTION; STEREOVISION;

AUTOMOTIVE ENGINEERING; IMAGE RECONSTRUCTION; PARKING; ROBUSTNESS (CONTROL SYSTEMS);

IMAGE SEGMENTATION;

EID: 29544443856     PISSN: 11108657     EISSN: None     Source Type: Journal    
DOI: 10.1155/ASP.2005.2322     Document Type: Article

References (15)

1. T. Suzuki and T. Kanada, "Measurement of vehicle motion and orientation using optical flow," in Proc. IEEE/IEEJ/JSAI International Conference on Intelligent Transportation Systems (ITSC '99), pp. 25-30, Tokyo, Japan, October 1999.
2. Z. Hu and K. Uchimura, "Tracking cycle: a new concept for simultaneous tracking of multiple moving objects in a typical traffic scene," in Proc. IEEE Intelligent Vehicles Symposium (IV '00), pp. 233-239, Dearborn, Mich, USA, October 2000.
3. N. Ancona, "A fast obstacle detection method based on optical flow," in Proc. European Conference on Computer Vision (ECCV '92), pp. 267-271, Santa Mangherita Ligure, Italy, May 1992.
4. D. Willersinn and W. Enkelmann, "Robust obstacle detection and tracking by motion analysis," in Proc. IEEE Conference on Intelligent Transportation System (ITSC '97), pp. 717-722, Boston, Mass, USA, November 1997.
5. U. Franke and A. Joos, "Real-time stereo vision for urban traffic scene understanding," in Proc. IEEE Intelligent Vehicles Symposium (IV '00), pp. 273-278, Dearborn, Mich, USA, October 2000.
6. U. Franke and S. Heinrich, "Fast obstacle detection for urban traffic situations," IEEE Trans. Intell. Transport. Syst., vol. 3, no. 3, pp. 173-181, 2002.
7. S. Bohrer, T. Zielke, and V. Freiburg, "An integrated obstacle detection framework for intelligent cruise control on motorways," in Proc. IIEEE Intelligent Vehicles Symposium (IV '95), pp. 276-281, Detroit, Mich, USA, September 1995.
8. M. Bertozzi and A. Broggi, "GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection," IEEE Trans. Image Processing, vol. 7, no. 1, pp. 62-81, 1998.
9. M. Bertozzi, A. Broggi, and A. Fascioli, "Stereo vision-based vehicle detection," in Proc. IEEE Intelligent Vehicles Symposium (IV '00), pp. 39-44, Dearborn, Mich, USA, October 2000.
10. M. Betke, E. Haritaoglu, and L. S. Davis, "Multiple vehicle detection and tracking in hard realtime," in Proc. IEEE Intelligent Vehicles Symposium (IV '96), pp. 351-356, Tokyo, Japan, September 1996.
11. T. Kalinke, C. Tzomakas, and W. V. Seelen, "A Texture-based object detection and an adaptive model-based classification," in Proc. IEEE Intelligent Vehicles Symposium (IV '98), vol. 1, pp. 143-148, Stuttgart, Germany, October 1998.
12. Y. Fang and I. Masaki, "Depth-based target segmentation for intelligent vehicles: fussion of radar and binocular stereo," IEEE Trans. Intell. Transport. Syst., vol. 3, no. 3, pp. 196-202, 2002.
13. W. E. L. Grimson, "Computational experiments with a feature based stereo algorithm," IEEE Trans. Pattern Anal. Machine Intell, vol. 7, no. 1, pp. 17-34, 1985.
14. T. Kanade and M. Okutomi, "A stereo matching algorithm with an adaptive window: theory and experiment," IEEE Trans. Pattern Anal. Machine Intell., vol. 16, no. 9, pp. 920-932, 1994.
15. T. Kanade, A. Yoshida, K. Oda, H. Kano, and M. Tanaka, "A stereo machine for video-rate dense depth mapping and its new applications," in Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '96), pp. 196-202, San Francisco, Calif, USA, June 1996.