Most existing approaches detect the vanishing point by voting the local dominant texture orientation at each pixel. However, when it is hard to distinguish natural road clues (items for finding the vanishing point) from background noises (e.g. stones, grasses) in complex scenes, they may suffer deteriorated accuracy and efficiency. In this paper, we introduce a novel vanishing point detection algorithm with the proposed Weber Orientation Descriptor (WOD). We first employ the differential excitation component of WOD to extract reliable road clue regions from a complex background, and then adopt the orientation component of WOD and our proposed line-voting scheme (LVS) to locate the vanishing point. Experimental results on the benchmark dataset reveal a step forward in detection performance against the state-of-the-art vanishing point detection methods.