Computer-Aided Imagery in Sport and Exercise: A Case Study of Indoor Wall Climbing

Abstract

Movement artificial intelligence of simulated humanoid characters has been advancing rapidly through joint efforts of the computer animation, robotics, and machine learning communitites. However, practical real-life applications are still rare. We propose applying the technology to mental practice in sports, which we denote as computer-aided imagery (CAI). Imagery, i.e., rehearsing the task in one's mind, is a difficult cognitive skill that requires accurate mental simulation; we present a novel interactive computational sport simulation for exploring and planning movements and strategies. We utilize a fully physically-based avatar with motion optimization that is not limited by a movement dataset, and customize the avatar with computer vision measurements of user's body. We evaluate the approach with 20 users in preparing for real-life wall climbing. Our results indicate that the approach is promising and can affect body awareness and feelings of competence. However, more research is needed to achieve accurate enough simulation for both gross-motor body movements and fine-motor control of the myriad ways in which climbers can grasp climbing holds or shapes.