Object recognition and pose estimation using color cooccurrence histograms and geometric modeling

Major contributions of the proposed system are the ability to automatically initiate an object tracking process, its robustness and invariance towards scaling and translations as well as the computational efficiency since both recognition and pose estimation rely on the same representation of the object. The performance of the system is evaluated in a domestic environment with changing lighting and background conditions on a set of everyday objects.