The interest of graph matching techniques in the pattern recognition field is increasing due to the versatility of representing knowledge in the form of graphs. However, the size ...
In this paper, we develop a geometric framework for linear or nonlinear discriminant subspace learning and classification. In our framework, the structures of classes are conceptu...
This paper introduces our one-armed stationary humanoid robot GripSee together with research projects carried out on this platform. The major goal is to have it analyze a table sce...
The aim of this paper is to present a dissimilarity measure strategy by which a new philosophy for pattern classification pertaining to dissimilaritybased classifications (DBCs) ca...
We present a taxonomy for local distance functions where most existing algorithms can be regarded as approximations of the geodesic distance defined by a metric tensor. We categor...