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In this paper we address the problems of virtual object interaction and user tracking in a

The MagicBook is a Mixed Reality interface that uses a real book to seamlessly transport users between Reality and Virtuality. A vision-based tracking method is used to overlay virtual models on real book pages, creating an Augmented Reality (AR) scene. When users see an AR scene they are interested in they can fly inside it and experience it as an immersive Virtual Reality (VR). The interface also supports multi-scale collaboration, allowing multiple users to experience the same virtual en vironment either from an egocentric or an exocentric perspective. In this paper we describe the MagicBook prototype, potential applications and user response.

Blending reality and virtuality, these interfaces let users see each other, along with virtual objects, allowing communication behaviors much more like face-to-face than like screen-based collaboration.

In this paper, we argue for embodied corrversational characters as the logical extension of the metaphor of human -computer interaction as a conversation. We argue that the only way to fully model the richness of human I&+ to-face communication is to rely on conversational analysis that describes sets of conversational behaviors as fi~lfilling conversational functions, both interactional and propositional. We demonstrate how to implement this approach in Rea, an embodied conversational agent that is capable of both multimodal input understanding and output generation in a limited application domain. Rea supports both social and task-oriented dialogue. We discuss issues that need to be addressed in creating embodied conversational agents, and describe the architecture of the Rea interface.

Abstract.Recently there has been an increase in research towards using hand gestures for interaction in the field of Augmented Reality (AR). These works have primarily focused on researcher designed gestures, while little is known about user preference and behavior for gestures in AR. In this paper, we present our guessability study for hand gestures in AR in which 800 gestures were elicited for 40 selected tasks from 20 participants. Using the agreement found among gestures, a user-defined gesture set was created to guide designers to achieve consistent user-centered gestures in AR. Wobbrock's surface taxonomy has been extended to cover dimensionalities in AR and with it, characteristics of collected gestures have been derived. Common motifs which arose from the empirical findings were applied to obtain a better understanding of users' thought and behavior. This work aims to lead to consistent user-centered designed gestures in AR.