BRIDGE：通过具身转换实现无边界的包容性与多样性游戏体验
BRIDGE: Borderless Reconfiguration for Inclusive and Diverse Gameplay Experience via Embodiment Transformation
AI总结：
BRIDGE通过具身转换技术提升残疾人体育的包容性和多样性，增强姿态自然性和战术意图理解，促进公平的战术资源获取。
摘要：
残疾人体育训练资源有限，减少了运动员和教练与运动特定动作和战术协调互动的机会。为解决这一缺口，我们开发了BRIDGE系统，该系统整合了重建流程，从广播视频中检测和跟踪球员以生成3D比赛序列，与一个具身感知的可视化框架相结合，该框架将头部、躯干和轮椅基座的方位分解以表示注意力、意图和移动性。我们通过两项受控研究评估了BRIDGE，参与人数为20人（10名国家级轮椅篮球队运动员和10名业余运动员）。结果显示，BRIDGE显著增强了球员姿态的感知自然性，并使战术意图更容易理解。此外，它通过真实传达球员的能力支持功能分类，从而提高了参与者的自我效能感。这项工作推动了包容性体育学习和可及性教练实践，为残疾人体育中的战术资源更公平获取做出了贡献。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
