Recognizing 3D Objects Using Photometric Invariant

In this paper we describe a new e cient algorithm for recognizing 3D objects by combining photometric and geometric invariants. Some photometric properties are derived, that are invariant to the changes of illumination and to relative object motion with respect to the camera and/or the lighting source in 3D space. We argue that conventional color constancy algorithms can not be used in the recognition of 3D objects. Further we show recognition does not require a full constancy of colors, rather, it only needs somethingthat remains unchanged under the varying light conditions and poses of the objects. Combining the derived color invariants and the spatial constraints on the object surfaces, we identify corresponding positions in the model and the data space coordinates, using centroid invariance of corresponding groups of feature positions. Tests are given to show the stability and e ciency of our approach to 3D object recognition. Copyright c Massachusetts Institute of Technology, 199...

• Type: Conference
• Year: 1995
• Where: ICCV
• Authors: Kenji Nagao
• Keywords: Arti Cial Intelligence, Computer Vision, Conventional Color Constancy, ICCV 1995, Relative Object Motion