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

## TL;DR

EVA is a real-time algorithm that generates emotionally expressive virtual agents by mapping gait and gaze features to perceived emotions, enhancing presence in multi-agent VR environments.

## Contribution

The paper introduces EVA, a novel real-time method for creating emotionally expressive virtual agents using gait and gaze features, with a data-driven emotion mapping.

## Key findings

- EVA can generate hundreds of virtual agents with emotional behaviors in real-time.
- Using gait and gaze features increases perceived emotional authenticity.
- Enhanced sense of presence in multi-agent VR scenarios.

## Abstract

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.