Expressing Personality Through Non-verbal Behaviour in Real-Time Interaction

The attribution of traits plays an important role as a heuristic for how we interact with others. Many psychological models of personality are analytical in that they derive a classification from reported or hypothesised behaviour. In the work presented here, we follow the opposite approach: Our personality model generates behaviour that leads an observer to attribute personality characteristics to the actor. Concretely, the model controls all relevant aspects of non-verbal behaviour such as gaze, facial expression, gesture, and posture. The model, embodied in a virtual human, affords to realistically interact with participants in real-time. Conceptually, our model focuses on the two dimensions of extra/introversion and stability/neuroticism. In the model, personality parameters influence both, the internal affective state as well as the characteristic of the behaviour execution. Importantly, the parameters of the model are based on empirical findings in the behavioural sciences. To evaluate our model, we conducted two types of studies. Firstly, passive experiments where participants rated videos showing variants of behaviour driven by different personality parameter configurations. Secondly, presential experiments where participants interacted with the virtual human, playing rounds of the Rock-Paper-Scissors game. Our results show that the model is effective in conveying the impression of the personality of a virtual character to users. Embodying the model in an artificial social agent capable of real-time interactive behaviour is the only way to move from an analytical to a generative approach to understanding personality, and we believe that this methodology raises a host of novel research questions in the field of personality theory.

Real-Time Capture of Snowboarder’s Skiing Motion Using a 3D Vision Sensor

Due to the influence of environmental interference and too fast speed, there are some problems in ski motion capture, such as inaccurate motion capture, motion delay, and motion loss, resulting in the inconsistency between the actual motion of later athletes and the motion of virtual characters. To solve the above problems, a real-time skiing motion capture method of snowboarders based on a 3D vision sensor is proposed. This method combines the Time of Fight (TOF) camera and high-speed vision sensor to form a motion acquisition system. The collected motion images are fused to form a complete motion image, and the pose is solved. The pose data is bound with the constructed virtual character model to drive the virtual model to synchronously complete the snowboarding motion and realize the real-time capture of skiing motion. The results show that the motion accuracy of the system is as high as 98.6%, which improves the capture effect, and the motion matching proportion is better and more practical. It is also excellent in the investigation of motion delay and motion loss.

3D Modeling Design of Multirole Virtual Character Based on Visual Communication in Wireless Sensor Networks

In order to solve the problems of poor design effect and time consumption of traditional virtual character modeling design methods, a three-dimensional (3D) modeling design method of multirole virtual characters based on visual communication is studied. Firstly, the wireless sensor network is used to locate, scan, and collect the human body structure information and convert the coordinates to bind the 3D skeleton. Secondly, according to different human postures, we switch the linear hybrid skin algorithm, spherical hybrid skin algorithm, and double quaternion hybrid skin algorithm; design the geometric surface; and attach it to the 3D skeleton to generate 3D modeling. Finally, based on the influence of visual communication on human eye observation and psychological feeling, the geometric surface is divided twice, and the virtual character is rendered in the way of display, coating, and splicing to obtain a complete 3D modeling of the virtual character. The results show that the positioning coverage of this method is higher, the rendering effect of the hand and head is better, the design time is significantly shortened, and the maximum time is no more than 35 min.

Design of Gradual Contemporary Wayang Visual Character Indonesia For Sticker Chatting And Game Applications

UNESCO international recognition in 2003 stated that wayang is one of Indonesia's cultural heritage, but the sense of belonging for wayang is still low among the nation's next generation of Indonesia. So at this time, both the government and the educators, still working to improve the regeneration of wayang knowledge and recognition for the young nation and the world, including through game application. In this study, the researchers created a contemporary virtual character of wayang, and will be inserted as a character sticker chatting and game application. This wayang virtual characters can be used as tools for reintroduction to young people around the world. This method will be conducted by researchers include depictions classification of facial expressions of emotion, collaborate with simplified visual approach, to obtain the corresponding visual characteristics of the wayang virtual characters. Researchers also used visual basic character as a prototype for contemporary form deformation, so it can be applied to the target games application and communication functions.

Exposure to robotic virtual agent affects adoption of intentional stance

Understanding how and when humans attribute intentionality to artificial agents is a key issue in contemporary human and technological sciences. This paper addresses the question of whether adopting intentional stance can be modulated by exposure to a 3D animated robot character, and whether this depends on the human-likeness of the character's behavior. We report three experiments investigating how appearance and behavioral features of a virtual character affect humans’ attribution of intentionality toward artificial social agents. The results show that adoption of intentional stance can be modulated depending on participants' expectations about the agent. This study brings attention to specific features of virtual agents and insights for further work in the field of virtual interaction.

Social Presence Outside the Augmented Reality Field of View

Augmented reality headsets in use today have a large area in which the real world can be seen, but virtual content cannot be displayed. Users perceptions of content in this area is not well understood. This work studies participants perception of a virtual character in this area by grounding this question in relevant theories of perception and performing a study using both behavioral and self-report measures. We find that virtual characters within the augmented periphery receive lower social presence scores, but we do notfind a difference in task performance. These findings inform application design and encourage future work in theories of AR perception and perception of virtual humans.

Developing an Analysis Framework for Studies on Pedagogical Agent in an e-Learning Environment

Pedagogical agents (PAs) are a crucial aspect of the e-learning environment. A PA is defined as a virtual character presented on an interface, and they are designed to promote student learning. PAs have been widely discussed in academic papers. However, an appropriate analysis framework has not been proposed because of the diversity and complexity of PAs. Therefore, we reviewed the literature and proposed a list of related clues, including environmental, learner, role, appearance, and social clues. We used this framework to analyse the learning effectiveness of PAs in specific areas. The keyword ‘pedagogical agent’ was used to search for related papers from 2000 to 2019. A total of 136 related papers were obtained. A meta-analysis was performed using a random effects model (Hedges’ g was used to measure the effect size). The effect size of the learning effectiveness of PA was small to medium (g = 0.423). The results of subgroup analysis (Hedges’s g) revealed that subjects, grades, additional support, appearance style, and facial expression changes had a different moderating effect on the effect of PA on learning effectiveness. We discussed the moderating effect of related clues and suggested future research directions.