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We are interested in developing real-time applications such as games or virtual prototyping that take advantage of the user full-body input to control a wide range of entities, from a self-similar avatar to any type of animated characters, including virtual humanoids with differing size and proportions. The key issue is, as always in real-time interactions, to identify the key factors that should get computational resources for ensuring the best user interaction efficiency. For this reason we first recall the definition and scope of such essential terms as immersion and presence, while clarifying the confusion existing in the fields of Virtual Reality and Games. This is done in conjunction with a short literature survey relating our interaction efficiency goal to key inspirations and findings from the field of Action Neuroscience. We then briefly describe our full-body real-time postural control with proactive local collision avoidance. The concept of obstacle spherification is introduced both to reduce local minima and to decrease the user cognitive task while interacting in complex environments. Finally we stress the interest of the egocentric environment scaling so that the user egocentric space matches the one of a height-differing controlled avatar. [ABSTRACT FROM AUTHOR]

This paper describes preliminary results of a research performed in the framework of the Enactive project (EU IST NoE Enactive). The aim of this research is to improve believability of a virtual character using qualitative analysis of gesture. Using techniques developed for human gesture analysis, we show it is possible to extract high-level motion features from reconstructed motion and to compare them with the same features extracted from the corresponding real motions. Moreover this method allows us to evaluate whether the virtual character conveys the same high level expressive content as the real motion does, and makes it possible to compare different rendering techniques in order to assess which one better maintains such information. [ABSTRACT FROM AUTHOR]

In this paper we explore the potential of Prioritized Inverse Kinematics for motion capture and postural control. We have two goals in mind: reducing the number of sensors to improve the usability of such systems, and allowing interactions with the environment such as manipulating objects or managing collisions on the fly. To do so, we enforce some general constraints such as balance or others that we can infer from the intended movement structure. On one hand we may loose part of the expressiveness of the original movement but this is the price to pay to ensure more precise interactions with the environment. [ABSTRACT FROM AUTHOR]