Recovering Surface Layout from an Image

Humans have an amazing ability to instantly grasp the overall 3D structure of a scene – ground orientation, relative positions of major landmarks, etc – even from a single image. This ability is completely missing in most popular recognition algorithms, which pretend that the world is flat and/or view it through a patch-sized peephole. Yet it seems very likely that having a grasp of this “surface layout” of a scene should be of great assistance for many tasks, including recognition, navigation, and novel view synthesis. In this paper, we take the first step towards constructing the surface layout, a labeling of the image into geometric classes. Our main insight is to learn appearance-based models of these geometric classes, which coarsely describe the 3D scene orientation of each image region. Our multiple segmentation framework provides robust spatial support, allowing a wide variety of cues (e.g., color, texture, and perspective) to contribute to the confidence in each ge...

• Type: Journal
• Year: 2007
• Where: IJCV
• Authors: Derek Hoiem, Alexei A. Efros, Martial Hebert
• Keywords: Geometric Classes, IJCV 2007, Images, Surface Layout