Semantic perception, as one of our central research themes, refers to any perceptual process semantically enabled for different purposes. The semantic perception has increasingly being considered as a salient feature, and at the same time, the main challenge in the development of intelligent interactive systems. The focus of our research in this theme concerns methods and approaches that aim towards bridging the gap between perceptual data and meaningful semantic knowledge. More specifically, our research range over machine sensing modalities, techniques for extracting and learning perceptual representations, and semantic grounding (or anchoring), in order to derive representative semantic knowledge about the perceived world (from the viewpoint of a machine). Another aspect of our interest in semantic perception is on the autonomous acquisition of (context-related) knowledge used to enrich the representation of a given set of data. For the purpose of automating the knowledge acquisition process, our approach in semantic representation is relying on ontological techniques. However, due to the inevitable and non-trivial trade-off between expressivity of representation models and the complexity of the reasoning process upon the semantics, our research concerns, last but not least, the development of reasoning techniques applicable to the represented semantics of the perceived data.
Keywords:
- semantic knowledge
- ontological techniques
- knowledge representation and reasoning
- perceptual anchoring
- machine sensing modalities.
Projects
Semantic Robots
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Take Back the Night
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E-care@home
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