3D vehicle sensor based on monocular vision

作者: Daniel Ponsa , Antonio López , Felipe Lumbreras , Joan Serrat , Thorsten Graf

DOI: 10.1109/ITSC.2005.1520204

关键词:

摘要: Determining the position of other vehicles on road is a key information to help driver assistance systems increase driver's safety. Accordingly, work presented in this paper addresses problem detecting front our own one and estimating their 3D by using single monochrome camera. Rather than predefined high level image features as symmetry, shadow search, etc., proposal for vehicle detection based learning process that determines, from training set, which are best distinguish non-vehicles. To compute with camera point consists knowing where horizon projects onto image. However, can change every frame difficult determine. In we study coupling between perceived actual width order reduce uncertainty estimated derived an unknown horizon.

参考文章(6)
S. Agarwal, A. Awan, D. Roth, Learning to detect objects in images via a sparse, part-based representation IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 26, pp. 1475- 1490 ,(2004) , 10.1109/TPAMI.2004.108
Richard Hartley, Andrew Zisserman, Multiple view geometry in computer vision ,(2000)
A. Broggi, P. Cerri, P.C. Antonello, Multi-resolution vehicle detection using artificial vision ieee intelligent vehicles symposium. pp. 310- 314 ,(2004) , 10.1109/IVS.2004.1336400
M. Maurer, R. Behringer, S. Furst, F. Thomanek, E.D. Dickmanns, A compact vision system for road vehicle guidance international conference on pattern recognition. ,vol. 3, pp. 313- 317 ,(1996) , 10.1109/ICPR.1996.546962
P. Viola, M. Jones, Rapid object detection using a boosted cascade of simple features computer vision and pattern recognition. ,vol. 1, pp. 511- 518 ,(2001) , 10.1109/CVPR.2001.990517
Richard Hartley, Andrew Zisserman, Multiple View Geometry in Computer Vision (2nd ed) Cambridge University Press. ,(2003)