Modeling Data-Driven Dominance Traits for Virtual Characters using Gait Analysis
We present a data-driven algorithm for generating gaits of virtual characters with varying dominance traits. Our gait dominance classification algorithm can classify the dominance traits of gaits with 73% accuracy. We also present an application of our approach that simulates interpersonal relationships between virtual characters. To the best of our knowledge, ours is the first practical approach to classifying gait dominance and generate dominance traits in virtual characters.