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Learning Responses to Visual Stimuli: A Generic Approach

Ellis, Liam ; Bowden, Richard

The 5th International Conference on Computer Vision Systems, 2007
Bielefeld, 21. - 24. März 2007

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Abstract:
A general framework for learning to respond appropriately to visual stimulus is presented. By hierarchically clustering percept-action exemplars in the action space, contextually important features and relationships in the perceptual input space are identified and associated with response models of varying generality. Searching the hierarchy for a set of best matching percept models yields a set of action models with likelihoods. By posing the problem as one of cost surface optimisation in a probabilistic framework, a particle filter inspired forward exploration algorithm is employed to select actions from multiple hypotheses that move the system toward a goal state and to escape from local minima. The system is quantitatively and qualitatively evaluated in both a simulated shape sorter puzzle and a real-world autonomous navigation domain.


Keywords: autonomous, control, generic-problem-solving
Institution: Faculty of Technology, Research Groups in Informatics
DDC classification: Data processing, computer science, computer systems

Suggested Citation:
Ellis, Liam ; Bowden, Richard  (2007)  Learning Responses to Visual Stimuli: A Generic Approach. The 5th International Conference on Computer Vision Systems, 2007


URL: http://biecoll.ub.uni-bielefeld.de/volltexte/2007/22



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