Self-calibration three-dimension reconstruction model of traffic accident photographs

LU Guang-quan; XU Hong-guo; MA She-qiang; LI Yi-bing

Volume 6 Issue 3

Turn off MathJax

Article Contents

Article Navigation > Journal of Traffic and Transportation Engineering > 2006 > 6(3): 109-113

Next Previous

LU Guang-quan, XU Hong-guo, MA She-qiang, LI Yi-bing. Self-calibration three-dimension reconstruction model of traffic accident photographs[J]. Journal of Traffic and Transportation Engineering, 2006, 6(3): 109-113.

Citation:

LU Guang-quan, XU Hong-guo, MA She-qiang, LI Yi-bing. Self-calibration three-dimension reconstruction model of traffic accident photographs[J]. Journal of Traffic and Transportation Engineering, 2006, 6(3): 109-113.

Citation:

PDF( 304 KB)

Self-calibration three-dimension reconstruction model of traffic accident photographs

1.
State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
2.
School of Transportation, Jilin University, Changchun 130025, Jilin, China
3.
Department of Traffic Management Engineering, Chinese People's Public Security University, Beijing 102614, China

More Information

Author Bio:
Lu Guang-quan(1974-), male, PhD, associate professor, 86-10-62772721, lugq@tsinghua.edu.cn
Received Date: 2006-02-27
Publish Date: 2006-09-25

Abstract

Abstract

In order to survey traffic accident scene rapidly, a 3-D reconstruction model of traffic accident scene based on self-calibration using general digital camera was explored.The model was based on fundamental matrix, which was estimated by matched feature points, essential matrix can be calculated by it.Traffic accident scene was reconstructed after essential matrix was decomposed.It is proved that the traffic accident scene can be reconstructed without calibration reference points in scene, the difference between the reconstruction result and real 3-D data is only a scale factor.
- traffic safety,
- traffic accident,
- analysis of photographs,
- three-dimension reconstruction,
- self-calibration,
- fundamental matrix

FullText(HTML)

References(8)

References

[1]	Qiao Xiang-ming, Xu An, Shu Wei. Developing tendency forecast of road traffic accident in China[J]. Journal of Chang'an University: Natural Science Edition, 2004, 24 (6): 64-66. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL200406016.htm
[2]	王丰元. 计算机视觉在道路交通事故现场勘查中的应用研究[D]. 北京: 中国农业大学, 1997.
[3]	Wang Feng-yuan, Yu Ren-de, Du Shou-xu. Photogrammetric principle and model test for road traffic accident scene measurement[J]. China Journal of Highway and Transport, 2001, 14 (1): 100-105. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL200101022.htm
[4]	Xu Hong-guo, Lu Guang-quan. Application of photogrammetry to measurement of traffic accident scene[A]//Proceedings of the Third International Conference on Traffic and Transportation Studies[C]. New York: American Society of Civil Engineers, 2002.
[5]	Hartley Richard I. Estimation of relative camera positions for uncalibrated cameras[A]//Proceeding of European Conferenceon Computer Vision[C]. Hamburg: Springer-Verlag, 1992.
[6]	Zhang Zheng-you. Determining the epipolar geometry and its uncertainty[J]. International Journal of Computer Vision, 1998, 27 (2): 161-195.
[7]	Fusiello A. Uncalibrated euclidean reconstruction[J]. Image and Vision Computing, 2000, 18 (7): 555-563.
[8]	Tang Chi-keung, Medioni Ge rard, Lee Mi-Suen. N-dimensional tensor voting and application to epipolar geometry estimation[J]. IEEE Transaction on Pattern Analysis and Machine Intelligence, 2001, 23 (8): 829-844. doi: 10.1109/34.946987