Range estimation from Intensity Gradient Analysis

Abstract

Conventional approaches to recovering depth from gray-level imagery have involved obtaining two or more images, applying an “interest” operator, and solving the correspondence problem. Unfortunately, the computational complexity involved in feature extraction and solving the correspondence problem makes existing techniques unattractive for many real-world robotic applications. By approaching the problem from more of an engineering perspective, we have developed a new depth recovery technique that completely avoids the computationally intensive steps of feature selection and correspondence required by conventional approaches. The Intensity Gradient Analysis technique (IGA) is a depth recovery algorithm that exploits the properties of the MCSO (moving camera, stationary objects) scenario. Depth values are obtained by analyzing temporal intensity gradients arising from the optic flow field induced by known camera motion. In doing so, IGA avoids the feature extraction and correspondence steps of conventional approaches and is therefore very fast. A detailed description of the algorithm is provided along with experimental results from complex laboratory scenes.