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Abstract-This work studies, implements and evaluates a gestures recognition module based on discrete Hidden Markov Models. The module is implemented on Matlab and used from Virtools. It can be used with different inputs therefore serves different recognition purposes. We focus on the 3D positions, our devices common information, as inputs for gesture recognition. Experiments are realized with an infra-red tracked flystick. Finally, the recognition rate is more than 90% with a personalized learning base. Otherwise, the results are beyond 70%, for an evaluation of 8 users on a real time mini-game. The rates are basically 80% for simple gestures and 60% for complex ones.

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This work focuses on enabling 3D interaction assistance by adding adaptivity depending on the tasks, objectives, and the general interaction context. We model the context using Conceptual Graphs (CG) based on an ontology. Including CG in our scene manager (Virtools) allows us to add semantic information and to describe the available tools. We handle rules leading to adaptation with a logic programming layer (Prolog+CG) included in the Amine platform. This project is a step towards Intelligent Virtual Environments, which proposes a hybrid solution by adding a separate semantic reasoning to classic environments. The first case study automatically manages few modalities depending on the distance to objects, user movement, available tools and modality risks.

Abstract:This work focuses on 3D interaction assistance by adding adaptivity depending on the tasks, the objectives, and the general interaction context. The context is modelled with Conceptual Graphs (CG) based on an ontology. Including CG in our scene manager (Virtools) allows us to add semantic information and to describe the available tools. Adaptation result from rules handled with a logic programming layer (Prolog+CG) included in the Amine platform. This project is a step towards Intelligent Virtual Environments, which proposes a hybrid solution by adding a separate semantic reasoning to classic environments. The first experiment automatically manages few modalities depending on the distance to objects, user movement, available tools and modalities.