Scene Edge Classification from Image Sequences

There is often interest in identifying geometry in a scene. Edge detection is an established method of looking at scene geometry, but naive edge detection in a complex scene discerns little about the physical geometry; light and shadowing effects especially in outdoor scenes can cause edge detectors to mistakenly classify texture and shadow edges as geometry edges. However, with a sample of several images of a scene where the illumination is changing over time, one can correctly classify different scene edges by removing lighting effects and textures. We present a method of using intrinsic images and time varying intensity gradient to identify geometry edges, texture edges and shadow edges. We first remove shadows, then look at per pixel gradient intensity variance to segment normals in the scene, and use the boundaries of those segments to find geometry edges. The texture edges then are the edges which have not been classified as geometry or shadow.