Interactive Locomotion Style Control for a Human Character based on Gait Cycle Features

This article introduces a data-driven locomotion style controller for full-body human characters using gait cycle features. Based on gait analysis, we define a set of gait features that can represent various locomotion styles as spatio-temporal patterns within a single gait cycle. We compute the gait features for every single gait cycle in motion capture data and use them to search for the desired motion. Our real-time style controller provides users with visual feedback for the changing inputs, exploiting the Motion Matching algorithm. We also provide a graphical controller interface that visualizes our style representation to enable intuitive control for users. We show that the proposed method is capable of retrieving appropriate locomotions for various gait cycle features, from simple walking motions to single-foot motions such as hopping and dragging. To validate the effectiveness of our method, we conducted a user study that compares the usability and performance of our system with those of an existing footstep animation tool. The results show that our method is preferred over the baseline method for intuitive control and fast visual feedback. We propose a data-driven locomotion style controller for full-body human characters using gait cycle features. Based on gait analysis, we define spatio-temporal gait features that can represent various locomotion styles and design a real-time style controller by utilizing them as control parameters.image