BRIDGE: Borderless Reconfiguration for Inclusive and Diverse Gameplay Experience via Embodiment Transformation

2026-02-26

AI Summary

This study addresses the scarcity of specialized motion and tactical coordination resources in para-sports training by proposing an innovative approach that integrates 3D athlete motion reconstruction with embodied perception visualization. Leveraging broadcast videos, the method reconstructs 3D poses and decomposes them into head, torso, and wheelchair orientations to explicitly represent attention, intention, and mobility capabilities. By uniquely combining multi-part pose decomposition with 3D reconstruction, this work not only significantly enhances the naturalness of reconstructed poses and the interpretability of tactical intent but also enables functional classification assessment. The approach effectively strengthens athletes’ self-efficacy and enriches their training experience in adaptive sports contexts.

Technology Category

• Computer Vision: Motion & Tracking
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning

Application Category

• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

Training resources for parasports are limited, reducing opportunities for athletes and coaches to engage with sport-specific movements and tactical coordination. To address this gap, we developed BRIDGE, a system that integrates a reconstruction pipeline, which detects and tracks players from broadcast video to generate 3D play sequences, with an embodiment-aware visualization framework that decomposes head, trunk, and wheelchair base orientations to represent attention, intent, and mobility. We evaluated BRIDGE in two controlled studies with 20 participants (10 national wheelchair basketball team players and 10 amateur players). The results showed that BRIDGE significantly enhanced the perceived naturalness of player postures and made tactical intentions easier to understand. In addition, it supported functional classification by realistically conveying players'capabilities, which in turn improved participants'sense of self-efficacy. This work advances inclusive sports learning and accessible coaching practices, contributing to more equitable access to tactical resources in parasports.

Problem

• parasports
• inclusive gameplay
• tactical training
• embodiment transformation
• accessible coaching

Innovation

• embodiment transformation
• 3D motion reconstruction
• inclusive sports technology
• wheelchair basketball
• tactical visualization