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Towards a Theoretical Framework for Learning Multi-modal Patterns for Embodied Agents

Noceti, N; Caputo, B; Castellini, C; Baldassarre, L; Barla, A; Rosasco, L; Odone, F; (2009) Towards a Theoretical Framework for Learning Multi-modal Patterns for Embodied Agents. In: Foggia, P and Sansone, C and Vento, M, (eds.) IMAGE ANALYSIS AND PROCESSING - ICIAP 2009, PROCEEDINGS. (pp. 239 - 248). SPRINGER-VERLAG BERLIN

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Abstract

Multi-modality is a fundamental feature that characterizes biological systems and lets them achieve high robustness in understanding skills while coping with uncertainty. Relatively recent studies showed that multi-modal learning is a potentially effective add-on to artificial systems, allowing the transfer of information from one modality to another. In this paper we propose a general architecture for jointly learning visual and motion patterns: by means of regression theory we model a mapping between the two sensorial modalities improving the performance of artificial perceptive systems. We present promising results on a case study of grasp classification in a controlled setting and discuss future developments.

Type: Proceedings paper
Title: Towards a Theoretical Framework for Learning Multi-modal Patterns for Embodied Agents
Event: 15th International Conference on Image Analysis and Processing (ICIAP 2009)
Location: Vietri sul Mare, ITALY
Dates: 2009-09-08 - 2009-09-11
ISBN-13: 978-3-642-04145-7
Keywords: multi-modality, visual and sensor-motor patterns, regression theory, behavioural model, objects and actions recognition, SCALE
UCL classification: UCL > School of BEAMS > Faculty of Engineering Science > Computer Science
URI: http://discovery.ucl.ac.uk/id/eprint/144211
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