Recognizing objects on the ground-plane

摘要

Objects such as vehicles are often constrained to lie on a known plane. The ground-plane constraint reduces the problem of localization and recognition from 6 to 3 DOF. A novel algorithm is presented which makes effective use of the ground-plane constraint to derive pose estimates. A form of the generalized Hough transform is used to group evidence from line features, and to identify approximate poses. The single orientation parameter is decoupled from the two location parameters, and dealt with separately. The method is fast and robust. It copes well with complex outdoor scenes including multiple occluded objects, and image clutter from irrelevant structures.