We view the task of change detection as a problem of object recognition from learning. The object is defined in a 3D space where the time is the 3rd dimension. We propose two com...
— In this paper we describe an efficient software architecture for object-tracking, based on a stereoscopic vision system, that has been applied to a mobile robot controlled by ...
Davide Scaramuzza, Stefano Pagnottelli, Paolo Vali...
We present a novel approach to the matching of subgraphs for object recognition in computer vision. Feature similarities between object model and scene graph are complemented with ...
Abstract. Markov and Conditional random fields (CRFs) used in computer vision typically model only local interactions between variables, as this is computationally tractable. In t...
The recognition of script in historical documents requires suitable techniques in order to identify single words. Segmentation of lines and words is a challenging task because lin...