Year: 2012
Type: dissertation
Abstract: Virtual Characters are more than avatars capable of expressing emotions and interact with the users. Virtual Characters should be seen as a very reliable representation of a human being, capable of expressing all the possible affective traits after the appraisal and evaluation of what is happening around and inside them. They should feel and express what they are feeling; they should convince you they are “real”. To achieve this level of believability several researchers have proposed different computational and affective models, as well as graphical techniques to simulate expressions, gestures, behavior or voice. All this state of art has provided us with sufficient data and information to see what else needs to be done. As a result, we propose a contextual and affective framework that allows the generation of the context that surrounds the character as well as the simulation of its psychological characteristics like preferences, standards, personality, or admiration for other agents. Moreover, the framework proposes novel and implementation independent techniques for the visualization of emotions and mood. Through experimentation we come up with a set of head-position/eye-gaze configurations that are perceived as certain personality traits, we validate the generation of expressions for moods, and assessed the feasibility of the context generation through movie scenes, which translated into our system, triggered the same emotions and elicit the same facial expressions as in the movie. This research is a step forward in the creation of more believable virtual characters, by pointing out other elements that should be considered when creating characters that can be used in affective HCI applications, storytelling, or virtual worlds for entertainment (e.g. Videogames) or for therapies (e.g. in therapies with autistic children)
Authors: Arellano Tavara, Diana Di Lorenza
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2517211868