A-Contrario Horizon-First Vanishing Point
Detection Using Second-Order Grouping Laws
Abstract. We show that, in images of man-made environments, the
horizon line can usually be hypothesized based on a-contrario detections
of second-order grouping events. This allows constraining the extraction
of the horizontal vanishing points on that line, thus reducing false detections. Experiments made on three datasets show that our method, not
only achieves state-of-the-art performance w.r.t. horizon line detection
on two datasets, but also yields much less spurious vanishing points than
the previous top-ranked methods