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.
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