Recursive 3-D Road and Relative Ego-State Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Vision-based autonomous road vehicles
Vision-based vehicle guidance
Optical flow estimation: advances and comparisons
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Control of visually guided behaviors
Real-time computer vision
Design and Implementation of the PAPRICA Parallel Architecture
Journal of VLSI Signal Processing Systems
Rapidly Adapting Machine Vision for Automated Vehicle Steering
IEEE Expert: Intelligent Systems and Their Applications
GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection
IEEE Transactions on Image Processing
Cellular Automata Based Inverse Perspective Transform as a Tool for Indoor Robot Navigation
AI*IA '99 Proceedings of the 6th Congress of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence
On-Road Vehicle Detection: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Traversable terrain classification for outdoor autonomous robots using single 2D laser scans
Integrated Computer-Aided Engineering - Informatics in Control, Automation and Robotics
A cascade of boosted generative and discriminative classifiers for vehicle detection
EURASIP Journal on Advances in Signal Processing
WSEAS Transactions on Computers
A DSP-based lane departure warning system
MMACTEE'06 Proceedings of the 8th WSEAS international conference on Mathematical methods and computational techniques in electrical engineering
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The use of microprocessors to control various automobile operations is now commonplace, and further computerization can be expected as researchers extend their efforts to develop autonomous, self-guided vehicles. One of the most challenging research areas is road following, which requires the two basic functionalities of lane detection and obstacle detection. Thanks to the reduced costs of image acquisition devices and to the increasing computational power of current computer systems, computer vision has recently become a popular method for sensing the surrounding environment. The authors use an approach that extracts and localizes features of interest, thereby limiting the computation-intensive processing of images. A geometrical transform called inverse perspective mapping makes a SIMD (single instruction, multiple data) approach practical for processing data captured in stereo images. Besides contributing to obstacle detection, the left stereo image is used in lane detection. The use of a 3D surface called a horopter, moved onto the road plane by electronic vergence, makes it possible to locate obstacles and establish their distance and exact position in 3D world space. The authors describe the GOLD system, a stereo vision system developed at the University of Parma, Italy, for generic obstacle detection and lane localization. GOLD was first tested on an experimental land vehicle for more than 3,000 kilometers along extra-urban roads and freeways at speeds up to 80 kilometers per hour and is now being ported to the Argo autonomous passenger vehicle.