A method for unrestricted recognition of three-dimensional objects was developed. By
unrestricted, we imply that the recognition will be done independently of object position …

In this paper we present a computationally efficient framework for part-based modeling and
recognition of objects. Our work is motivated by the pictorial structure models introduced by …

Pattern recognition involves the correct recognition of an object irrespective of rotation, scale
and translation. In this paper the authors have come up with a recognition scheme, that has …

We address the problem of automatically learning object models for recognition and pose
estimation. In contrast to the traditional approach, we formulate the recognition problem as …

Image-based techniques for object recognition have recently been developed to recognize a
specific three-dimensional object after a 'learning'stage, in which a few two-dimensional …

In computer vision, the indexing problem is the problem of recognizing a few objects in a
large database of objects while avoiding the help of the classical image-feature-to-object …

The systems and concepts described in this paper document the evolution of the geometric
invariance approach to object recognition over the last five years. Invariance overcomes one …

We present different training algorithms for radial basis function (RBF) networks. The
behaviour of RBF classifiers in three different pattern recognition applications is presented …

Automatie object recognition is a multidisciplinary research area using con cepts and tools
from mathematics, computing, optics, psychology, pattern recognition, artificial intelligence …

Pairwise geometric histogram (PGH) based algorithms have previously been shown to be a
robust solution for the recognition of arbitrary 2D shapes in the presence of occlusion and …