A controlling strategy for an active vision system based on auditory and visual cues

Authors:
Miranda Grahl;Frank Joublin;Franz Kummert
Affiliations:
Cor-Lab, Bielefeld University, Bielefeld, Germany;Honda Research Institute Europe GmbH, Offenbach, Germany;Cor-Lab, Bielefeld University, Bielefeld, Germany
Venue:
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part II
Year:
2010

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Abstract

It is still an open question how preliminary visual reflexes can be structured by auditory and visual modalities in order to recognize objects. Therefore, we propose a new method for a controlling strategy for an active vision system that learns to focus on relevant multi modal aspects of the environment. The method is bootstrapped by a bottom up visual saliency process in order to extract important visual points. In this paper, we present our first results and focus on the unsupervised generation of training data for a multi-modal object recognition. The performance is compared to a human evaluated database.