Unrestricted Recognition of 3-D Objects for Robotics Using Multi-Level Triplet Invariants

A method for unrestricted recognition of 3-D objects has been developed. By unrestricted, we imply that the recognition shall be done independently of object position, scale, orientation and pose, ...

[1]  William Grimson,et al.  Object recognition by computer - the role of geometric constraints , 1991 .

[2]  Andrew Zisserman,et al.  Geometric invariance in computer vision , 1992 .

[3]  Gösta H. Granlund,et al.  The complexity of vision , 1999, Signal Process..

[4]  Cordelia Schmid,et al.  Local Grayvalue Invariants for Image Retrieval , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Ronen Basri,et al.  Recognition by Linear Combinations of Models , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Gösta H. Granlund,et al.  An Associative Perception-Action Structure Using a Localized Space Variant Information Representation , 2000, AFPAC.

[7]  Tomaso Poggio,et al.  Image Representations for Visual Learning , 1996, Science.

[8]  Mohammed Bennamoun,et al.  Representation and Recognition of 3D Free-Form Objects , 2002, Digit. Signal Process..

[9]  Björn Johansson,et al.  Fast Selective Detection of Rotational Symmetries Using Normalized Inhibition , 2000, ECCV.

[10]  Isaac Weiss,et al.  Model-Based Recognition of 3D Objects from Single Images , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Ramesh C. Jain,et al.  Three-dimensional object recognition , 1985, CSUR.

[12]  Hiroshi Murase,et al.  Visual learning and recognition of 3-d objects from appearance , 2005, International Journal of Computer Vision.

[13]  T. Poggio,et al.  A network that learns to recognize three-dimensional objects , 1990, Nature.

[14]  Hans Knutsson,et al.  Signal processing for computer vision , 1994 .

[15]  Heinrich Niemann,et al.  Neural networks for the recognition and pose estimation of 3D objects from a single 2D perspective view , 2001, Image Vis. Comput..

[16]  Cordelia Schmid,et al.  Evaluation of Interest Point Detectors , 2000, International Journal of Computer Vision.

[17]  Andrea J. van Doorn,et al.  Invariant Properties of the Motion Parallax Field due to the Movement of Rigid Bodies Relative to an Observer , 1975 .

[18]  David G. Lowe,et al.  Local feature view clustering for 3D object recognition , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[19]  Tomaso Poggio,et al.  Computational Models of Object Recognition in Cortex: A Review , 2000 .

[20]  Alex Pentland,et al.  Probabilistic object recognition and localization , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[21]  Linda G. Shapiro,et al.  Triplet-based object recognition using synthetic and real probability models , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[22]  Jiri Matas,et al.  Object Recognition using the Invariant Pixel-Set Signature , 2000, BMVC.

[23]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[24]  Harry Wechsler,et al.  A paradigm for invariant object recognition of brightness, optical flow and binocular disparity images , 1982, Pattern Recognit. Lett..

[25]  K. Kanatani Camera rotation invariance of image characteristics , 1987 .

[26]  Gösta H. Granlund Does Vision Inevitably Have to be Active , 1998 .

[27]  Marcus Isaksson Face Detection and Pose Estimation using Triplet Invariants , 2002 .