  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.
