Geometric invariance in computer vision
Geometric invariance in computer vision
Geometric invariants and object recognition
International Journal of Computer Vision
Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
International Journal of Computer Vision
Foundations of semi-differential invariants
International Journal of Computer Vision
SIAM Journal on Numerical Analysis
Computing Size Functions from Edge Maps
International Journal of Computer Vision
Algebraic and Geometric Tools to Compute Projective and Permutation Invariants
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing 3D Objects Using Tactile Sensing and Curve Invariants
Journal of Mathematical Imaging and Vision
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
The Geometry of Multiple Images: The Laws That Govern The Formation of Images of A Scene and Some of Their Applications
Some recent results on the projective evolution of 2-D curves
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 3)-Volume 3 - Volume 3
Geometric Level Set Methods in Imaging,Vision,and Graphics
Geometric Level Set Methods in Imaging,Vision,and Graphics
Projective analysis of 2-D images
IEEE Transactions on Image Processing
Retrieval of trademark images by means of size functions
Graphical Models - Special issue on the vision, video and graphics conference 2005
Describing shapes by geometrical-topological properties of real functions
ACM Computing Surveys (CSUR)
Multidimensional Size Functions for Shape Comparison
Journal of Mathematical Imaging and Vision
Palm-print recognition by matrix discriminator
Expert Systems with Applications: An International Journal
A global method for reducing multidimensional size graphs
GbRPR'11 Proceedings of the 8th international conference on Graph-based representations in pattern recognition
A new algorithm for computing the 2-dimensional matching distance between size functions
Pattern Recognition Letters
Persistence modules, shape description, and completeness
CTIC'12 Proceedings of the 4th international conference on Computational Topology in Image Context
Hi-index | 0.00 |
For comparison of shapes under subgroups of the projective group, we can use a lot of invariants and especially differential invariants coming from multiscale analysis. But such invariants, as we have to compute curvature, are very sensitive to the noise induced by the dicretization grid. In order to resolve this problem we use size functions which can recognize the “qualitative similarity” between graphs of functions that should be theorically coinciding but, unfortunately, change their values due to the presence of noise. Moreover, we focus this study on a projective differential invariant which allows to decide if one shape can be considered as the deformation of another one by a rotation of the camera.