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Original scientific paper

3D Road Scene Interpretation for Autonomous Vehicle Driving

Gian Luca Foresti ; Department of Mathematics and Computer Science (DIMI), University of Udine, Italy
Carlo Regazzoni ; Department of Biophysical and Electronic Engineering (DIBE), University of Genova, Italy

Fulltext: english, pdf (7 MB) pages 277-294 downloads: 162* cite
APA 6th Edition
Foresti, G.L. & Regazzoni, C. (1999). 3D Road Scene Interpretation for Autonomous Vehicle Driving. Journal of computing and information technology, 7 (4), 277-294. Retrieved from https://hrcak.srce.hr/130482
MLA 8th Edition
Foresti, Gian Luca and Carlo Regazzoni. "3D Road Scene Interpretation for Autonomous Vehicle Driving." Journal of computing and information technology, vol. 7, no. 4, 1999, pp. 277-294. https://hrcak.srce.hr/130482. Accessed 24 Oct. 2020.
Chicago 17th Edition
Foresti, Gian Luca and Carlo Regazzoni. "3D Road Scene Interpretation for Autonomous Vehicle Driving." Journal of computing and information technology 7, no. 4 (1999): 277-294. https://hrcak.srce.hr/130482
Harvard
Foresti, G.L., and Regazzoni, C. (1999). '3D Road Scene Interpretation for Autonomous Vehicle Driving', Journal of computing and information technology, 7(4), pp. 277-294. Available at: https://hrcak.srce.hr/130482 (Accessed 24 October 2020)
Vancouver
Foresti GL, Regazzoni C. 3D Road Scene Interpretation for Autonomous Vehicle Driving. Journal of computing and information technology [Internet]. 1999 [cited 2020 October 24];7(4):277-294. Available from: https://hrcak.srce.hr/130482
IEEE
G.L. Foresti and C. Regazzoni, "3D Road Scene Interpretation for Autonomous Vehicle Driving", Journal of computing and information technology, vol.7, no. 4, pp. 277-294, 1999. [Online]. Available: https://hrcak.srce.hr/130482. [Accessed: 24 October 2020]

Abstracts
In this paper, the problem of 3D road scene interpretation for autonomous vehicle driving is addressed. In particular, the problems of road detection and obstacle avoidance in outdoor environments are investigated. A set of descriptive primitives (straight and circular line segments) is selected to describe 3D objects which commonly occur in road scenes, e.g., people, cars, trucks, houses, etc. First, these primitives are extracted directly from the input image of the scene, and then are grouped according to specific geometric relationships (symmetry, convergence, parallelism, closeness, etc.). Relational geometrical knowledge of the elements of a group can be used to index an object in a pure bottom-up way, so decreasing the recognition complexity by reducing the amount of data to be matched with an object model database. Results on a road image containing obstacles, which show the efficiency, accuracy and time performances of the proposed method are reported.

Keywords
Image processing; feature extraction; feature grouping; autonomous vehicle driving

Hrčak ID: 130482

URI
https://hrcak.srce.hr/130482

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