Paper Info
Title
Road Type Estimation and Hierarchical Real-Time Vanishing Point Detection
Abstract
Image-based road vanishing point (VP) detection is a challenging problem as the algorithm needs to deal with different road type with varying imaging conditions in real time. We propose a hierarchical VP detection method with the ability to choose efficient algorithms for different road types. Firstly, road scenes are classified into 4 types based on holistic road features abstracted from responses of Gabor filters, which also coarsely locate the road. Then, the distinct edge or line-like texture of each road type is adaptively extracted by a new road-line-segment detection method. Finally, VP is estimated by road-type-specific voting and verification. Experiments on 1000 general road images show that, the proposed method can detect VP under complex road scenes, achieving improvements for both accuracy and efficiency, compared with the state of the art methods relying on single features.
Year
DOI
Venue
2013
10.1109/ICIG.2013.73
ICIG
Keywords
Field
DocType
new road-line-segment detection method,holistic road,road type estimation,gabor filters,hierarchical real-time vanishing point detection,image-based road,line like texture extraction,different road type,roads,vanishing point,art method,road type,hierarchical real-time vanishing point,gabor filter,road types,road scene,image-based road vanishing point detection,feature extraction,image classification,complex road scene,edge detection,general road image,line-segment detection,object detection,natural scenes,holistic road feature extraction,holistic feature,road line segment detection method,image texture,hierarchical vp detection method,road scene classification,adaptive edge extraction,algorithm design and analysis,estimation
Computer vision,Object detection,Algorithm design,Voting,Pattern recognition,Computer science,Image texture,Edge detection,Feature extraction,Artificial intelligence,Contextual image classification,Vanishing point
Conference
Citations 
PageRank 
References 
1
0.36
7
Authors
3
Name
Order
Citations
PageRank
Yuan Sun121322.75
Hongbo Lu231.81
Zhimin Zhang36814.94