Robust regression and outlier detection
Robust regression and outlier detection
VITS-A Vision System for Autonomous Land Vehicle Navigation
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special Issue on Industrial Machine Vision and Computer Vision Technology:8MPart
Applications of dynamic monocular machine vision
Machine Vision and Applications
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
Finding road lane boundaries for vision-guided vehicle navigation
Vision-based vehicle guidance
A parallel architecture for curvature-based road scene classification
Vision-based vehicle guidance
Integrated Premission Planning and Execution for Unmanned Ground Vehicles
Autonomous Robots - Special issue on autonomous agents
Computer Vision and Image Understanding - Special issue on event detection in video
Driver Assistance System Based on Monocular Vision
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
Hi-index | 0.98 |
The YARF system extracts road features from color images in order to drive a vehicle along the road. Central to the system is a model of the road which includes both geometric information about the relative placement of the features defining the lane structure of the road and information about the appearance of those features. This model is used to selectively apply specialized image segmentation methods to perform the feature detection; to provide the system of constraints which relate the feature positions to the vehicle position on the road; and to provide a context of expectations about the appearance of the road which can be used to analyze situations where expected features are not seen. Experimental results are presented showing the benefit of using multiple specialized image segmentation techniques, the advantages of using Least Median Squares estimation in situations where there are outliers in the data, and the ability of YARF to detect intersections and changes in lane structure based on the failure to see expected features in the image.