DocumentCode
2634786
Title
Efficient image gradient-based object localisation and recognition
Author
Tan, T.N. ; Sullivan, G.D. ; Baker, K.D.
Author_Institution
Dept. of Comput. Sci., Reading Univ., UK
fYear
1996
fDate
18-20 Jun 1996
Firstpage
397
Lastpage
402
Abstract
This paper reports novel algorithms for the efficient localisation and recognition of vehicles in traffic scenes, which eliminate the need for explicit symbolic feature extraction and matching. The algorithms make use of two a priori sources of knowledge about the scene and the objects: (i) the ground-plane constraint, and (ii) the fact that road vehicles are strongly rectilineal: The algorithms are demonstrated and tested using routine outdoor traffic images. Success with a variety of vehicles demonstrates the efficiency and robustness of context-based computer vision in road traffic scenes. The limitations of the algorithms are also addressed in the paper
Keywords
computer vision; object recognition; road traffic; traffic engineering computing; computer vision; feature extraction; image gradient-based; object localisation; recognition of vehicles; road traffic scenes; traffic images; Computer science; Computer vision; Feature extraction; Image recognition; Land vehicles; Layout; Road vehicles; Robustness; Solid modeling; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition, 1996. Proceedings CVPR '96, 1996 IEEE Computer Society Conference on
Conference_Location
San Francisco, CA
ISSN
1063-6919
Print_ISBN
0-8186-7259-5
Type
conf
DOI
10.1109/CVPR.1996.517103
Filename
517103
Link To Document