While interactive virtual humans are becoming widely used in education, training and therapeutic applications, building animations which are both realistic and parameterized in respect to a given scenario remains a complex and time-consuming task. In order to improve this situation, we propose a framework based on the direct demonstration and parameterization of motions. The presented approach addresses three important aspects of the problem in an integrated fashion: (1) our framework relies on

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... an interactive real-time motion capture interface that empowers non-skilled animators with the ability to model realistic upper-body actions and gestures by direct demonstration; (2) our interface also accounts for the interactive definition of clustered example motions, in order to well represent the variations of interest for a given motion being modeled; and (3) we also present an inverse blending optimization technique which solves the problem of precisely parameterizing a cluster of example motions in respect to arbitrary spatial constraints. The optimization is efficiently solved on-line, allowing autonomous virtual humans to precisely perform learned actions and gestures in respect to arbitrarily given targets. Our proposed framework has been implemented in an immersive multi-tile stereo visualization system, achieving a powerful and intuitive interface for programming generic parameterized motions by demonstration.