Exploring Non-verbal Behavior Models for Believable Characters.

Believable characters constitute an important component of interactive stories. It is, therefore, not surprising to see much research focusing on developing algorithms that enhance character believability within interactive experiences, such as games, interactive narrative, and training environments. These efforts target a variety of problems, including portraying and synchronizing gestures with speech, developing animation tools that allow artists to manipulate and blend motions, or embed emotions within virtual character models. There has been very little research, however, devoted to the study of non-verbal behaviors, specifically mannerisms, patterns of movement including postures, gaze, and timing, and how they vary as a function of character attributes. This paper presents a work in progress of a study conducted to (1) identify key character characteristics recognized by animators using an acting model, and (2) formalize non-verbal behaviors patterns that animators use to express these character characteristics

Creating adaptive and individual personalities in many characters without hand crafting behaviours

Believable characters significantly increase the immersion of users or players in interactive applications. A key component of believable characters is their personality, which has previously been implemented statically using the time consuming task of hand-crafting individuality for each character. Often personality has been modeled based on theories that assume behavior is the same regardless of situation and environment. This paper presents a simple affective and cognitive framework for interactive entertainment characters that allows adaptation of behavior based on the environment and emotions. Different personalities are reflected in behavior preferences which are generated based on individual experience. An initial version of the framework has been implemented in a simple scenario to explore which parameters have the greatest effect on agent diversity

A Cognitive Approach to Narrative Planning with Believable Characters

In this work, we address the question of generating understandable narratives using a cognitive approach. The requirements of cognitive plausibility are presented. Then an abduction-based cognitive model of the human deliberative reasoning ability is presented. We believe that implementing such a procedure in a narrative context to generate plans would increase the chances that the characters will be perceived as believable. Our suggestion is that the use of a deliberative reasoning procedure can be used as a basis of several strategies to generate interesting stories

Understanding virtual actors

Publicado em: "2010 Brazilian Symposium on Games and Digital Entertainment: SBGames 2010 : proceedings". ISBN 978-0-7695-4359-8Autonomous Digital Actors represent the next step in authoring movies with believable characters, in a way that will allow them to be trained for acting specific roles in a story, suggesting appropriate behaviors during their performance. This article presents an overview of the art of acting and directing and how these concepts were used to elaborate a Virtual Actor metaphor. Also, we present an agent architecture for describing and implementing the virtual actors’ acting knowledge base.(undefined

Kofifi/Covfefe: How the Costumes of Sophiatown Bring 1950s South Africa to Western Massachusetts in 2020

This thesis paper reflects upon the costume design process taken by Emma Hollows to produce a realist production of the Junction Avenue Theatre Company’s musical Sophiatown at the Augusta Savage Gallery at the University of Massachusetts in May 2020. Sophiatown follows a household forcibly removed from their homes by the Native Resettlement Act of 1954 amid apartheid in South Africa. The paper discusses her attempts as a costume designer to strike a balance between replicating history and making artistic changes for theatre, while always striving to create believable characters

How turn-taking influences the perception of a suspect in police interviews

We study turn-taking behaviour in non-cooperative dialogue for the development of believable characters in a serious game for conversational skill learning in the police interview context. We describe a perception study to see how participants perceive a suspect’s interpersonal stance, rapport, face, and deception when the turn-taking of the subject varies. We influence the perception of the suspect’s stance by altering the timing of the start of speech with respect to the ending of the interlocutor’s speech. The results of the study contribute to the development of an embodied conversational agent capable of natural human-system conversation with appropriate turn-taking behaviour