Recognition and localization of articulated objects

Presents a method for the localization and interpretation of modeled objects that is general enough to cover articulated and other types of constrained models. The flexibility between components of the model are expressed as spatial constraints which are fused into the pose estimation during the interpretation process. The constraint fusion assists in obtaining a precise and stable pose of each object's component and in finding the correct interpretation. The proposed method can handle any constraint (including inequalities) between any number of different components of the model. The framework is based on Kalman filtering.<>