Objective
The classical approach to artificial intelligence in vision, has faced many fundamental problems. Progress was made in very specific and strictly-controlled application domains only. On the other hand, during recent years a tremendous amount of new biological evidence has been brought about by visual neuroscience which could be used for developing artificial vision systems.
This project proposes a new 3D object recognition system that will reconcile state-of-the-art computer vision techniques with neurobiological and psychophysical evidence of visual perception. Active vision, i.e. including intentional observer motion in the visual process, will be implemented based on locally-autonomous and self-organising brain-style neural networks.
The aim of this project is to realise a working system which can recognize many (i.e. more than 100) types of natural or everyday 3D-objects, in a way which is invariant to changes in the presentation of the objects or to the presence of structural noise in the input.
Fields of science
Topic(s)
Call for proposal
Data not availableFunding Scheme
RGI - Research grants (individual fellowships)Coordinator
100 44 STOCKHOLM
Sweden