Life-Sized Audiovisual Spatial Social Scenes with Multiple Characters: MARC & SMART-I²

International audienceWith the increasing use of virtual characters in virtual and mixed reality settings, the coordination of realism in audiovisual rendering and expressive virtual characters becomes a key issue. In this paper we introduce a new system combining two systems for tackling the issue of realism and high quality in audiovisual rendering and life-sized expressive characters. The goal of the resulting SMART-MARC platform is to investigate the impact of realism on multiple levels: spatial audiovisual rendering of a scene, appearance and expressive behaviors of virtual characters. Potential interactive applications include mediated communication in virtual worlds, therapy, game, arts and elearning. Future experimental studies will focus on 3D audio/visual coherence, social perception and ecologically valid interaction scenes

Emotions, behaviour and belief regulation in an intelligent guide with attitude

Abstract unavailable please refer to PD

Gender stereotypes in virtual agents

Visual, behavioural and verbal cues for gender are often used in designing virtual agents to take advantage of their cultural and stereotypical effects on the users. However, recent studies point towards a more gender-balanced view of stereotypical traits and roles in our society. This thesis is intended as an effort towards a progressive and inclusive approach for gender representations in virtual agents. The contributions are two-fold. First, in an iterative design process, representative male, female and androgynous embodied AI agents were created with few differences in their visual attributes. Second, these agents were then used to evaluate the stereotypical assumptions of gendered traits and roles in AI virtual agents. The results showed that, indeed, gender stereotypes are not as effective as previously assumed, and androgynous agents could represent a middle-ground between gendered stereotypes. The thesis findings are presented in the hope to foster discussions in virtual agent research and the frequent stereotypical use of gender representations

Process of character design for animated films: an analysis of elderly characters

Esta dissertação explora o processo de design de um personagem para um filme de animação. Tendo como referências os filmes de animação criados pela Disney e Pixar. De forma a focar os conceitos obtidos sobre o processo de design de personagens foi escolhido um grupo em específico de personagens para serem analisados, a escolha foram personagens idosos. Procurou-se perceber como é que os idosos são vistos pela sociedade contemporânea e vários autores académico referem que é dos grupos etários que mais sofre com preconceitos. Paralelamente a está pesquisa foram selecionadas várias personagens idosas de filmes de animação da Disney e Pixar, de modo a compreender como é que estas são representadas visualmente. No total de 86 filmes produzidos pela Disney e Pixar apenas 1 filme teve um idoso como personagem principal, Carl Fredericksen, de 78 anos. Carl é protagonista em Up (Docter, 2009) e por ser uma personagem tão peculiar e única foi analisado como caso de estudo. A metodologia utilizada foi baseada em literatura académica e documentários sobre design de personagens, a indústria da animação e sobre seniores. Vários filmes da Disney e Pixar foram visualizados e stills recolhidos para exemplificar os conteúdos explicados na dissertação. Esta dissertação procura explicar o processo de criação de um personagem para um filme de animação a qualquer pessoa interessada na área e pode ser também utilizada para a criação de um personagem senior. É importante criar personagens apelativas para que se diferenciem e fiquem na memória dos espectadores e a criação de mais personagens idosas em filmes de animação pode ajudar a combater estereótipos perante os idosos.This dissertation explores the process of character design for an animated film, having as references the animated films created by Disney and Pixar. In order to focus on the concepts obtained about the process of character design it was chosen a specific group of characters to be analysed, elderly characters. It was sought to understand how the elderly are seen by contemporary society and several academic authors refer that it is one of the age groups that suffers most ageism. In parallel to this research, several elderly characters from Disney and Pixar animated films were selected, in order to understand how they are visually represented. In the total of 86 films produced by Disney and Pixar, only 1 film had an elderly as the main character, Carl Fredericksen, 78 years old. Carl is the protagonist in Up (Docter, 2009) and because he is such a peculiar and unique character, he was analysed as a case study. The methodology used was based on academic literature and documentaries about character design, the animation industry, and about seniors. Several Disney and Pixar films were viewed and stills collected to exemplify the contents explained in the dissertation. This dissertation seeks to explain the process character design for an animated film to anyone interested in the area. It can also guide in the creation of a senior character. It is important to create unique and appealing characters that stay in the viewers’ memory, and the creation of more senior characters in animated films can help to combat stereotypes towards the elderly

Affective Computing

This book provides an overview of state of the art research in Affective Computing. It presents new ideas, original results and practical experiences in this increasingly important research field. The book consists of 23 chapters categorized into four sections. Since one of the most important means of human communication is facial expression, the first section of this book (Chapters 1 to 7) presents a research on synthesis and recognition of facial expressions. Given that we not only use the face but also body movements to express ourselves, in the second section (Chapters 8 to 11) we present a research on perception and generation of emotional expressions by using full-body motions. The third section of the book (Chapters 12 to 16) presents computational models on emotion, as well as findings from neuroscience research. In the last section of the book (Chapters 17 to 22) we present applications related to affective computing

A study of how the technological advancements in capturing believable facial emotion in Computer Generated (CG) characters in film has facilitated crossing the uncanny valley

A Research Report submitted in partial fulfilment of the requirement for the Degree of Masters of Arts in Digital Animation at the University of the Witwatersrand (School of Digital Arts) Johannesburg, South AfricaIn recent years, the quest for capturing authentic emotion convincingly in computer generated (CG) characters to assist exceedingly complex narrative expressions in modern cinema has intensified. Conveying human emotion in a digital human-like character is widely accepted to be the most challenging and elusive task for even the most skilled animators. Contemporary filmmakers have increasingly looked to complex digital tools that essentially manipulate the visual design of cinema through innovative techniques to reach levels of undetectable integration of CG characters. In trying to assess how modern cinema is pursuing the realistic integration of CG human-like characters in digital film with frenetic interest despite the risk of box office failure associated with the uncanny valley, this report focuses on the progress of the advances in the technique of facial motion capture. The uncanny valley hypothesis, based on a theory by Sigmund Freud, was coined in 1970 by Japanese robotics professor, Masahiro Mori. Mori suggested that people are increasingly comfortable with robots the more human-like they appear, but only up to a point. At that turning point, when the robot becomes too human-like, it arouses feelings of repulsion. When movement is added to this equation, viewers’ sense of the uncanny is heightened when the movement is deemed to be unreal. Motion capture is the technique of mimicking and capturing realistic movement by utilising technology that enables the process of translating a live actor’s performance into a digital performance. By capturing and transferring the data collected from sensors placed on a body suit or tracked from a high definition video, computer artists are able to drive the movement of a corresponding CG character in a 3-Dimensional (3D) programme. The attention of this study is narrowed to the progress of the techniques developed during a prolific decade for facial motion capture in particular. Regardless of the conflicting discourse surrounding the use of motion capture technology, these phenomenal improvements have allowed filmmakers to overcome that aspect of the uncanny valley associated with detecting realistic movement and facial expression. The progress of facial motion capture is investigated through the lens of selected films released during the period of 2001 to 2012. The two case studies, The Curious Case of Benjamin Button (2008) and Avatar (2009) were chosen for their individual achievement and innovative techniques that introduced new methods of facial capture. Digital images are said to undermine the reality status of cinematic images by challenging the foundation of long held theories of cinematic realist theory. These theories rooted in the indexical basis of photography, have proved to be the origin of contemporary viewers' notion of cinematic realism. However, the relationship between advanced digital effects and modern cinematic realism has created a perceptual complexity that warrants closer scrutiny. In addressing the paradoxical effect that photo-real cinematic realism is having on the basic comprehension of realism in film, the history of the seminal claims made by recognized realist film theorists is briefly examined

A Study Of The Effects Of Computer Animated Character Body Style On Perception Of Facial Expression

This study examined if there is a difference in viewer perception of computer animated character facial expressions based on character body style, specifically, realistic and stylized character body styles. Participants viewed twenty clips of computer animated characters expressing one of five emotions: sadness, happiness, anger, surprise and fear. They then named the emotion and rated the sincerity, intensity, and typicality of each clip. The results indicated that for recognition, participants were more slightly more likely to recognize a stylized character although it was not a significant difference. Stylized characters were on average rated higher for sincerity and intensity and realistic characters were on average rated higher for typicality. A significant difference in ratings was shown with fear (within sincerity and typicality) having realistic characters rated higher, happiness (within sincerity and intensity) having stylized characters rated higher and stylized being rated higher once for anger (stylized) and realistic (typicality) being rated once for anger. Other differences were also noted within the dependent variables. Based on the data collected in this study, overall there was not a significant difference in participant ratings between the two character styles