Multimodal communication is key to smooth interactions between people. However, multimodality remains limited in current human-computer interfaces. For example, posture is less explored than other modalities, such as speech and facial expressions. The postural expressions of others have a huge impact on how we situate and interpret an interaction. Devices and interfaces for representing full-body interaction are available (e.g., Kinect and full-body avatars), but systems still lack computational models relating these modalities to spatial and emotional communicative functions.The goal of this thesis is to lay the foundation for computational models that enable better use of posture in human-computer interaction. This necessitates addressing several research questions: How can we symbolically represent postures used in interpersonal communication? How can these representations inform the design of virtual characters' postural expressions? What are the requirements of a model of postural interaction for application to interactive virtual characters? How can this model be applied in different spatial and social contexts?In our approach, we start with the manual annotation of video corpora featuring postural expressions. We define a coding scheme for the manual annotation of posture at several levels of abstraction and for different body parts. These representations were used for analyzing the spatial and temporal relations between postures displayed by two human interlocutors during spontaneous conversations.Next, representations were used to inform the design of postural expressions displayed by virtual characters. For studying postural expressions, we selected one promising, relevant component of emotions: the action tendency. Animations were designed featuring action tendencies in a female character. These animations were used as a social context in perception tests.Finally, postural expressions were designed for a virtual character used in an ambient interaction system. These postural and spatial behaviors were used to help users locate real objects in an intelligent room (iRoom). The impact of these bodily expressions on the user¡¯s performance, subjective perception and behavior was evaluated in a user studyFurther studies of bodily interaction are called for involving, for example, motion-capture techniques, integration with other spatial modalities such as gaze, and consideration of individual differences in bodily interaction.
