3D structures for generic object recognition

We discuss the issues and challenges of generic object recognition. We argue that high-level, volumetric part-based descriptions are essential in the process of recognizing objects that might never have been observed before, and for which no exact geometric model is available. We discuss the representation scheme and its relationships to the three main tasks to solve: extracting descriptions from real images, under a wide variety of viewing conditions; learning new objects by storing their description in a database; and recognizing objects by matching their description to that of similar previously observed objects.

[1]  I. Biederman.  Recognition-by-components: a theory of human image understanding. , 1987, Psychological review.

[2]  C. Huang,et al.  MORSE : A 3 D Object Recognition System Based on GeometricInvariantsJ , 1994 .

[3]  Ramakant Nevatia,et al.  Description and Recognition of Curved Objects , 1977, Artif. Intell..

[4]  R. Brooks.  Model-Based Three-Dimensional Interpretations of Two-Dimensional Images , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Mi-Suen Lee,et al.  A Computational Framework for Segmentation and Grouping , 2000 .

[6]  L. Stark,et al.  Dissertation Abstract , 1994, Journal of Cognitive Education and Psychology.

[7]  Emanuele Trucco,et al.  Geometric Invariance in Computer Vision , 1995 .

[8]  A. Macworth.  Interpreting pictures of polyhedral scenes , 1973 .

[9]  Gérard G. Medioni,et al.  The Challenge of Generic Object Recognition , 1994, Object Representation in Computer Vision.

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

[11]  Sven J. Dickinson,et al.  Panel report: the potential of geons for generic 3-D object recognition , 1997, Image Vis. Comput..

[12]  Shree K. Nayar,et al.  An Experimental Comparison of Appearance and Geometric Model Based Recognition , 1996, Object Representation in Computer Vision.

[13]  Thomas O. Binford,et al.  Bayesian inference in model-based machine vision , 1987, Int. J. Approx. Reason..

[14]  Gérard G. Medioni,et al.  Generic Shape Learning and Recognition , 1996, Object Representation in Computer Vision.

[15]  Azriel Rosenfeld,et al.  Recognition by Functional Parts , 1995, Comput. Vis. Image Underst..

[16]  Ramakant Nevatia,et al.  From an Intensity Image to 3-D Segmented Descriptions , 1996, Object Representation in Computer Vision.

[17]  T. Binford,et al.  Finding and recovering SHGC objects in an edge image , 1993 .

[18]  K NayarShree,et al.  Visual learning and recognition of 3-D objects from appearance , 1995 .

[19]  S. Sutherland.  Seeing things , 1989, Nature.

[20]  Jean Ponce,et al.  Invariant Properties of Straight Homogeneous Generalized Cylinders and Their Contours , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  Martial Hebert,et al.  Object Representation in Computer Vision II , 1996, Lecture Notes in Computer Science.

[22]  Jitendra Malik,et al.  Computing the aspect graph for line drawings of polyhedral objects , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[23]  Ramakant Nevatia,et al.  Three-Dimensional Descriptions Based on the Analysis of the Invariant and Quasi-Invariant Properties of Some Curved-Axis Generalized Cylinders , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[24]  A. Pentland.  Recognition by Parts , 1987 .

[25]  Alan K. Mackworth.  Interpreting Pictures of Polyhedral Scenes , 1973, IJCAI.

[26]  Ramakant Nevatia,et al.  Perception of 3-D Surfaces from 2-D Contours , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  David G. Lowe,et al.  Perceptual Organization and Visual Recognition , 2012 .

[28]  David J. Kriegman,et al.  Illumination cones for recognition under variable lighting: faces , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[29]  Robert Bergevin,et al.  Generic Object Recognition: Building and Matching Coarse Descriptions from Line Drawings , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[30]  Rodney A. Brooks,et al.  Model-Based Three-Dimensional Interpretations of Two-Dimensional Images , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.