<i>FVA:</i>Modeling Perceived Friendliness of Virtual Agents Using Movement Characteristics

Randhavane, Tanmay; Bera, Aniket; Kapsaskis, Kyra; Manocha, Dinesh

doi:10.1109/tvcg.2019.2932235

Cited by 23 publications

(15 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Studies concerning interaction between humans and virtual characters have interested the virtual reality community for the past few decades. [15][16][17] To understand interactions with virtual characters, subjective data may be collected using questionnaires, or objective data may be collected using various types of sensors (e.g., electroencephalograms, electrodermal sensors, eye-tracking sensors, and motion capture sensors). Such methods have been employed efficiently to understand such interactions.…”

Section: Related Workmentioning

confidence: 99%

Immersive walking in a virtual crowd: The effects of the density, speed, and direction of a virtual crowd on human movement behavior

Koilias

Nelson

Anagnostopoulos

et al. 2020

Computer Animation & Virtual

View full text Add to dashboard Cite

We investigated the movement behavior of participants walking within a virtual crowd in an immersive virtual environment. We investigated three different parameters that characterize a moving virtual crowd: density, speed, and direction. An immersive road-crossing scenario that took place in a virtual metropolitan city was created. In this scenario, the participants were instructed to walk toward the opposite sidewalk. Three measurements (speed, deviation, and trajectory length) were used to evaluate the impact of the parameters assigned to the virtual crowd on the movement behavior of the participants. Significant results were found for both the main and interaction effects. The results suggested that the high density, low speed, and diagonal direction situations associated with the virtual crowd had the greatest impacts on the speed, deviation, and trajectory lengths of participants when they walked in a virtual environment and were surrounded by a moving virtual population.

show abstract

Section: Related Workmentioning

confidence: 99%

Immersive walking in a virtual crowd: The effects of the density, speed, and direction of a virtual crowd on human movement behavior

Koilias

Nelson

Anagnostopoulos

et al. 2020

Computer Animation & Virtual

View full text Add to dashboard Cite

show abstract

“…Narang et al [44] studied self-recognition in virtual agents with walking gaits and avatars of real humans. Gaits have been used to convey friendliness [50] and dominance [51] of virtual agents. Gazing has been a focus of attention in many VR studies too [45,63].…”

Section: Expressive Features Of Virtual Agentsmentioning

confidence: 99%

EVA: Generating Emotional Behavior of Virtual Agents using Expressive Features of Gait and Gaze

Randhavane

Bera

Kapsaskis

et al. 2019

ACM Symposium on Applied Perception 2019

Self Cite

View full text Add to dashboard Cite

We present a novel, real-time algorithm, EVA, for generating virtual agents with various perceived emotions. Our approach is based on using Expressive Features of gaze and gait to convey emotions corresponding to happy, sad, angry, or neutral. We precompute a data-driven mapping between gaits and their perceived emotions. EVA uses this gait emotion association at runtime to generate appropriate walking styles in terms of gaits and gaze. Using the EVA algorithm, we can simulate gaits and gazing behaviors of hundreds of virtual agents in real-time with known emotional characteristics. We have evaluated the benefits in different multi-agent VR simulation environments. Our studies suggest that the use of expressive features corresponding to gait and gaze can considerably increase the sense of presence in scenarios with multiple virtual agents.

show abstract

“…Expressive verbal and non-verbal behaviors in virtual characters convey a wide range of traits such as friendliness and warmth [Randhavane et al 2019a], competence [Nguyen et al 2015, and gender [Vala et al 2011]; as well as increasing the sense of presence in virtual reality environments [Randhavane et al 2019b]. Appropriate speech and gaze increase the social presence in multi-party interaction [Yumak and Magnenat-Thalmann 2016].…”

Section: Expressive Agentsmentioning

confidence: 99%

A Conversational Agent Framework with Multi-modal Personality Expression

2021

View full text Add to dashboard Cite

Consistently exhibited personalities are crucial elements of realistic, engaging, and behavior-rich conversational virtual agents. Both nonverbal and verbal cues help convey these agents’ unseen psychological states, contributing to our effective communication with them. We introduce a comprehensive framework to design conversational agents that express personality through non-verbal behaviors like body movement and facial expressions, as well as verbal behaviors like dialogue selection and voice transformation. We use the OCEAN personality model, which defines personality as a combination of five orthogonal factors of openness, conscientiousness, extraversion, agreeableness, and neuroticism. The framework combines existing personality expression methods with novel ones such as new algorithms to convey Laban Shape and Effort qualities. We perform Amazon Mechanical Turk studies to analyze how different communication modalities influence our perception of virtual agent personalities and compare their individual and combined effects on each personality dimension. The results indicate that our personality-based modifications are perceived as natural, and each additional modality improves perception accuracy, with the best performance achieved when all the modalities are present. We also report some correlations for the perception of conscientiousness with neuroticism and openness with extraversion.

show abstract

FVA:Modeling Perceived Friendliness of Virtual Agents Using Movement Characteristics

Cited by 23 publications

References 51 publications

Immersive walking in a virtual crowd: The effects of the density, speed, and direction of a virtual crowd on human movement behavior

Immersive walking in a virtual crowd: The effects of the density, speed, and direction of a virtual crowd on human movement behavior

EVA: Generating Emotional Behavior of Virtual Agents using Expressive Features of Gait and Gaze

A Conversational Agent Framework with Multi-modal Personality Expression

Contact Info

Product

Resources

About