Marie Curie Intra-European Fellowships for Career Development, European Commission under the FP7 call reference FP7-PEOPLE-2012-IEF
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A challenging goal in cognitive vision research deals with integrating quantitative and qualitative representation; in particular, quantitative computer vision techniques for object recognition, tracking, etc., and qualitative spatio-temporal representations to abstract away from unnecessary details, noise, error and uncertainty. This project is aimed at developing a semantic and qualitative description of real-world scenes captured at the Cartesium, where the Spatial Cognition Research Centre at Universität Bremen is located. Computer vision techniques are applied to recognize objects in digital images. A qualitative model for describing scenes and spatio-temporal changes will be defined in order to manage uncertainty and to apply qualitative reasoning models for inferring further information. Then, the qualitative descriptions obtained will be provided with ontological meaning for symbol-grounding in order to provide scenario understanding to software or robotic agents. To enhance human-machine communication, the qualitative and semantic descriptions obtained will be translated to natural language and a narrative description will be provided to the end-user for reading or for listening to by means of a speech synthesizer program. Finally, as a cognitive system must have the ability to learn from sensor inputs, a framework for symbolic learning will be designed.