用智能手表与手势追踪融合，实现日常表面的精准触控交互。
SurfaceXR: Fusing Smartwatch IMUs and Egocentric Hand Pose for Seamless Surface Interactions
- 融合头显手部追踪与手表加速度计数据，互补提升精度。
- 21人实验显示，触控追踪与8类手势识别效果显著优于单一方式。
- 适合需要长时间操作的沉浸式应用开发者与研究者。
在扩展现实（XR）中，空中手势常导致疲劳和不精确。基于表面的交互虽更准确舒适，但现有以自我为中心的视觉方法受限于手部追踪困难和表面平面估计不可靠。我们提出SurfaceXR，一种结合头戴设备手部追踪与智能手表惯性测量单元（IMU）数据的传感器融合方案，实现在日常表面上的鲁棒输入。核心洞察在于：手部追踪提供3D位置信息，而IMUs捕捉高频运动信号。21名参与者的实验验证了SurfaceXR在触控追踪与8类手势识别上的有效性，相比单模态方法有显著提升。
原文摘要 · Abstract (English)
Mid-air gestures in Extended Reality (XR) often cause fatigue and imprecision. Surface-based interactions offer improved accuracy and comfort, but current egocentric vision methods struggle due to hand tracking challenges and unreliable surface plane estimation. We introduce SurfaceXR, a sensor fusion approach combining headset-based hand tracking with smartwatch IMU data to enable robust inputs on everyday surfaces. Our insight is that these modalities are complementary: hand tracking provides 3D positional data while IMUs capture high-frequency motion. A 21-participant study validates SurfaceXR's effectiveness for touch tracking and 8-class gesture recognition, demonstrating significant improvements over single-modality approaches.
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