Clicking is a key feature any interaction input system needs to provide. In the case of 3D input devices, such a feature is often difficult to provide (e.g. vision-based, or tracking systems for free-hand interaction do not natively provide any button). In this work, we show that it is actually possible to build an application that provides two classical interaction tasks (selection, and pick-release), without any button-like feature. Our method is based on trajectory and kinematic gesture analysis. In a preliminary study we exhibit the principle of the method. Then, we detail an algorithm to discriminate selection, pick and release tasks using kinematic criteria. We present a controlled experiment that validates our method with an average success rate equal to 90.1% across all conditions.
We are interested in multimodal systems that use the following modes and modalities: speech (and natural language) as input as well as output, gesture as input and visual as output using screen displays. The user exchanges with the system by gesture and/or oral statements in natural language. This exchange, encoded in the different modalities, carries the goal of the user and also the designation of objects (referents) needed to achieve this goal. The system must identify in a precise and non-ambiguous way the objects designated by the user. In this paper, our main concern is the multimodal designations, with possibly imprecise gesture, of objects in the visual context. In order to identify such a designation, we propose a solution which uses probabilities, knowledge about manipulated objects, and perceptive aspects (degree of salience) associated with these objects.
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