Effient Matching with Invariant Local Descriptors

We are addressing the problem of matching images of scene or of objects when a large collection of reference objects is considered. The paper addresses also the issue of dealing with illumination change and camera position changes. Our approach is firstly based on the use of invariants. Invariants have to be computed locally so that the resulting values will not affected by partial occlusion or accidental highlights. In- variants proved to be a very discriminant piece of information and stored in a hash table they allow efficient indexing of visual shape. Final recognition can be performed using simply a robust voting technique or can be improved using Bayesian decision.

[1]  Hans-Peter Kriegel,et al.  The X-tree : An Index Structure for High-Dimensional Data , 2001, VLDB.

[2]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[3]  Shree K. Nayar,et al.  Computing reflectance ratios from an image , 1993, Pattern Recognit..

[4]  Brian V. Funt,et al.  Colour Constancy for Scenes with Varying Illumination , 1996, ECCV.

[5]  Tony Lindeberg,et al.  Scale-Space Theory in Computer Vision , 1993, Lecture Notes in Computer Science.

[6]  Ramin Zabih,et al.  Non-parametric Local Transforms for Computing Visual Correspondence , 1994, ECCV.

[7]  Jin-Long Chen,et al.  Matching curved 3D object models to 2D images , 1994, Proceedings of 1994 IEEE 2nd CAD-Based Vision Workshop.

[8]  Roger Mohr,et al.  Non-parametric Invariants and Application to Matching , 1997 .

[9]  Robert C. Bolles,et al.  3DPO: A Three- Dimensional Part Orientation System , 1986, IJCAI.

[10]  Charles Poynton,et al.  Frequently Asked Questions about Color , 1997 .

[11]  M K Brown,et al.  The Extraction of Curved Surface Features with Generic Range Sensors , 1986 .

[12]  Alex Pentland,et al.  Face recognition using eigenfaces , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

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

[14]  Rakesh Mohan,et al.  Multidimensional Indexing for Recognizing Visual Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Bir Bhanu,et al.  Gabor wavelets for 3-D object recognition , 1995, Proceedings of IEEE International Conference on Computer Vision.

[16]  Stephen D. Shapiro,et al.  Feature space transforms for curve detection , 1978, Pattern Recognition.

[17]  Olivier D. Faugeras,et al.  HYPER: A New Approach for the Recognition and Positioning of Two-Dimensional Objects , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[18]  Kenji Nagao,et al.  Recognizing 3D objects using photometric invariant , 1995, Proceedings of IEEE International Conference on Computer Vision.

[19]  Kehang Chen,et al.  Three-dimensional object recognition , 1997 .

[20]  Cordelia Schmid,et al.  Appariement d'images par invariants locaux de niveaux de gris. Application à l'indexation d'une base d'objets. (Image matching by local greyvalue invariants. Applied to indexing an object database) , 1996 .

[21]  Paul A. Viola.  Feature-Based Recognition of Objects , 1993 .

[22]  Hiroshi Murase,et al.  Learning and recognition of 3D objects from appearance , 1993, [1993] Proceedings IEEE Workshop on Qualitative Vision.

[23]  Yehezkel Lamdan,et al.  Geometric Hashing: A General And Efficient Model-based Recognition Scheme , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[24]  Bernt Schiele,et al.  Probabilistic object recognition using multidimensional receptive field histograms , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[25]  Charlie Rothwell.  Object Recognition through Invariant Indexing , 1995 .

[26]  Brian V. Funt,et al.  Color Constant Color Indexing , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  Max A. Viergever,et al.  Higher Order Differential Structure of Images , 1993, IPMI.

[28]  Rajesh P. N. Rao,et al.  Object indexing using an iconic sparse distributed memory , 1995, Proceedings of IEEE International Conference on Computer Vision.

[29]  R. Mohr,et al.  What accuracy for 3D measurements with cameras? , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[30]  Glenn Healey,et al.  The Illumination-Invariant Recognition of 3D Objects Using Local Color Invariants , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[31]  Sameer A. Nene,et al.  A simple algorithm for nearest neighbor search in high dimensions , 1997 .

[32]  Andrew P. Witkin,et al.  Scale-Space Filtering , 1983, IJCAI.

[33]  Rakesh Mohan,et al.  Multidimensional indexing for recognizing visual shapes , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[34]  Bernt Schiele,et al.  Object Recognition Using Multidimensional Receptive Field Histograms , 1996, ECCV.