29.3. 本章小结#
本章围绕空间交互技术展开，梳理了从二维到三维交互的演进路径，并深入探讨了虚拟现实与增强现实中正在兴起的多通道智慧交互方式。我们看到，随着三维空间定位设备和三维显示技术的发展，交互的载体已从平面转向空间，用户不再局限于屏幕与按钮的操作，而是通过视线、语音、身体动作等更加自然的方式进入到数字环境之中。
在本章的前半部分，我们回顾了三维交互技术的演进，包括如何在经典交互设备的基础上实现空间操作、如何借助空间定位设备（如传感器、动作捕捉）实现更精准的控制，以及多模态感知和反馈系统如何协同构建智慧交互体验。随后，我们聚焦于虚拟现实（VR）和增强现实（AR）领域，讨论了这些技术如何重构用户与数字世界之间的界面，打造真正沉浸、动态、响应式的交互场景。
空间交互不仅是技术的延伸，更是人类感知和思维方式的拓展。随着相关硬件、算法与内容生态的不断成熟，空间交互将成为新一代人机关系的关键节点，也将为教育、设计、医疗、娱乐等领域带来颠覆式的变革。
29.3.1. 习题#
随着摄像头硬件的发展，基于普通网络摄像头的低成本眼动追踪方案逐渐出现（如基于机器学习的 gaze estimation）。 请简述这种方法相比传统红外反射式眼动仪有哪些技术优势和限制？在什么场景下更适合使用低成本方案？
在 VR/AR 应用中，越来越多系统尝试通过多通道交互方式增强用户的沉浸感。除了视线、语音、手势、触觉等通道，你还能想到哪些用于提高交互效率和交互自然度的通道？
如图 29.40 所示，[KRaRL25] 提出了一种戴在手腕上的肌电传感器设备，可以通过识别手部肌肉信号实现手势、导航、手写等输入操作，且无需用户个性化训练即可使用。
（1）这种基于 表面肌电（surface electromyography，sEMG） 的输入方式相比于手势识别等输入方式有什么优势？如果你要对此进行评估，你会如何设计实验，并关注哪些性能指标？
（2）相比于依赖摄像头或手柄等物理控制器的交互方式，基于肌电信号的交互能在遮挡、多任务或空间受限的 VR/AR 场景中提供更稳定、隐形且实时的输入。在实际应用中，你认为这种交互方式可能引发哪些问题，或面临哪些挑战？
图 29.40 论文《一种用于人机交互的通用非侵入性神经运动接口》（A generic noninvasive neuromotor interface for human-computer interaction）演示。[KRaRL25]#
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