Interactive Game Development and Evaluation Based on Device-Free Pose Estimation Techniques

Abstract

In recent years, significant advancements have been made in pose estimation methods. These methods can be broadly divided into two categories: device-based and device-free. Device-based methods, such as virtual reality data gloves and marker-based motion capture, are known for their accuracy. However, these require specific equipment, making them less accessible for the public. On the other hand, device-free methods need no device to recognize human movement. They usually use cameras and estimation algorithms to recognize the body parts. Owing to evolving artificial intelligence (AI) technology, estimation accuracy has increased and we adopt one of the device-free methods to develop two interactive games, “Brain Wall” and “Touch de Pose”. “Brain Wall” challenges players to imitate a silhouette, scoring them based on the accuracy of their pose compared to the silhouette using the Intersection over Union metric. The game encourages competitiveness and participation through a leader board system. “Touch de Pose” allows players to choose a pose theme and the players are required to position specific body parts within the displayed circles on the screen. “Touch de Pose” also includes real-time evaluation of the player’s pose and combines their image with themed background images generated by generative AI, some of which demonstrate the limitations of the technology. The games were showcased at a university open campus event, receiving overwhelmingly positive feedback: 95.6% satisfaction for “Brain Wall” and 98.1% for “Touch de Pose”. Our study shows that pose estimation-based interactive games show immense potential in generating interest in technology for those who are unfamiliar with information and communication technology. Additionally, the full-body engagement aspect of these games could also play a role in promoting physical activity as a regular habit.