Abstract: Methods and systems of identification of objects in query images are disclosed. Keypoints in the query images are identified corresponding to objects to be identified. Visual words are identified in a dictionary of visual words for the identified keypoints. A set of hits is identified corresponding to reference images comprising the identified keypoints. Reference images corresponding to the identified set of hits are ranked using clustering of matches in a limited pose space. The limited pose space comprises a one-dimensional table corresponding to the rotation between the object to be identified with respect to the reference image. A first subset of M reference images that obtained a rank above a predetermined threshold is then selected. Offline, hybrid and combined offline and hybrid systems for performing the proposed methods are disclosed.

Abstract: Methods and systems of identification of objects in query images are disclosed. Keypoints in the query images are identified corresponding to objects to be identified. Visual words are identified in a dictionary of visual words for the identified keypoints. A set of hits is identified corresponding to reference images comprising the identified keypoints. Reference images corresponding to the identified set of hits are ranked using clustering of matches in a limited pose space. The limited pose space comprises a one-dimensional table corresponding to the rotation between the object to be identified with respect to the reference image. A first subset of M reference images that obtained a rank above a predetermined threshold is then selected. Offline, hybrid and combined offline and hybrid systems for performing the proposed methods are disclosed.