Abstract
This paper proposes a method to localize a 3D object in cluttered environment. Model of the object is represented by local shape features, computed from some reference images. Localization is performed by stereo images captured simultaneously by a pair of calibrated cameras. First the object is recognized in both images, using the local shape features. Then common features are used for reconstruction of the 3D position of the object. The proposed localization method is robust to different kinds of geometric and photometric transformations in addition to cluttering, partial occlusions and background changes. The accuracy and efficiency of the method is good enough for many practical applications.