Visualizing Category-Specific Changes in Oblique Photographs of Mountain Landscapes

Abstract

Our paper proposes a method for visualizing the spatial distribution of classes for a multi-class image segmentation problem. We apply this method for the case of mountain landscape images, where classes are defined by landscape categories. The proposed method builds class-specific distribution maps. Our contribution is two-fold. First, the class-specific distribution maps allow for the visualization of class-specific changes computed from pairs of images depicting the same landscape at different moments in time. Second, these maps enable us to calculate prior class probabilities for statistical scene segmentation purposes.