Using the theory of correspondences from algebraic geometry, we develop methods to relate 3-D objects to 2-D images and vice versa. In effect, we provide a very general framework for the use of geometric invariants in image recognition. At the most concrete level, our techniques yield a system of polynomial equations in variables which represent both the 3-D invariants of the features on an object and the 2-D invariants of features in an image. These equations will be satisfied if and only if the object can produce the image up to affine transformations of both the object and the image. The case of projective invariants will be dealt with in a forthcoming paper. The applications considered are to single view recognition and to indexing imag...
This thesis introduces a novel representation for three-dimensional (3D) objects in terms of local a...
There is a fundamental relationship between projective geometry and the perspective imaging geometry...
This paper introduces a novel method, which utilizes local appearance descriptions in a more efficie...
Geometric invariants appear to play an important role in object recognition as an aid to building mo...
International audienceWe are interested in the applications of invariant theory to computer vision p...
International audienceWe are interested in the applications of invariant theory to computer vision p...
International audienceWe are interested in the applications of invariant theory to computer vision p...
International audienceWe are interested in the applications of invariant theory to computer vision p...
By organizing object recognition as indexing a look-up table of model object fea-tures, it can be ma...
This thesis concerns the general problem of three dimensional model-based vision. Our focus in this ...
no noteThis paper studies the invariant theory for its applications to computer vision. In the first...
Recent research has indicated that invariants can be useful in computer vision for identification an...
This article introduces a novel method for 3D object recognition, which utilizes well-known local fe...
International audienceThis article introduces a novel representation for three-dimensional (3D) obje...
We investigate the differences --- conceptually and algorithmically --- between affine and project...
This thesis introduces a novel representation for three-dimensional (3D) objects in terms of local a...
There is a fundamental relationship between projective geometry and the perspective imaging geometry...
This paper introduces a novel method, which utilizes local appearance descriptions in a more efficie...
Geometric invariants appear to play an important role in object recognition as an aid to building mo...
International audienceWe are interested in the applications of invariant theory to computer vision p...
International audienceWe are interested in the applications of invariant theory to computer vision p...
International audienceWe are interested in the applications of invariant theory to computer vision p...
International audienceWe are interested in the applications of invariant theory to computer vision p...
By organizing object recognition as indexing a look-up table of model object fea-tures, it can be ma...
This thesis concerns the general problem of three dimensional model-based vision. Our focus in this ...
no noteThis paper studies the invariant theory for its applications to computer vision. In the first...
Recent research has indicated that invariants can be useful in computer vision for identification an...
This article introduces a novel method for 3D object recognition, which utilizes well-known local fe...
International audienceThis article introduces a novel representation for three-dimensional (3D) obje...
We investigate the differences --- conceptually and algorithmically --- between affine and project...
This thesis introduces a novel representation for three-dimensional (3D) objects in terms of local a...
There is a fundamental relationship between projective geometry and the perspective imaging geometry...
This paper introduces a novel method, which utilizes local appearance descriptions in a more efficie...