发表机构
The Hong Kong Polytechnic University; The Chinese University of Hong Kong（香港理工大学; 香港中文大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文综述AI智能眼镜作为可穿戴智能平台，从自我中心感知到智能体个性化，提出四维框架并识别五大研究挑战。
AI 中文摘要
人工智能（AI）的最新进展正在将智能眼镜从自我中心捕获和显示设备重塑为可穿戴智能的平台。智能眼镜日益成为可穿戴AI系统，在严格的外形因素约束下，将第一人称观察与实时辅助连接起来。我们通过“AI智能眼镜”的视角来框定这一转变，并将其定义为一个系统级概念，其中自我中心感知、资源感知计算、智能推理、多模态交互和现实世界应用约束被协同设计，以在物理世界中提供个性化辅助。为系统研究这一视角，我们围绕四个相互关联的维度组织本综述。首先，我们考察限制感知、计算、反馈传递和持续部署的硬件基础。其次，我们研究可穿戴智能，其中自我中心信号被转化为感知、情境和智能体能力。第三，我们讨论交互设计，用户通过交互在持续活动中请求、接收、纠正和调节辅助。第四，我们分析跨医疗保健、无障碍、情境学习、日常生活辅助、文化旅游和工业支持的应用场景，展示领域需求如何重塑系统设计和评估。我们进一步识别未来AI智能眼镜的五个跨领域研究挑战：下一代硬件、可信自我中心智能、终身个性化记忆、主动智能和具身基础模型。通过将智能眼镜定位为可穿戴智能平台，本综述为组织这一新兴领域的技术、应用和开放挑战提供了统一框架。
英文摘要
Recent advances in artificial intelligence (AI) are reshaping smart glasses from egocentric capture and display devices into platforms for wearable intelligence. Smart glasses increasingly serve as wearable AI systems that connect first-person observation with real-time assistance under strict form-factor constraints. We frame this transition through the lens of \emph{AI smart glasses} and define them as a system-level concept in which egocentric sensing, resource-aware computing, intelligent reasoning, multimodal interaction, and real-world application constraints are co-designed for personalized assistance in the physical world. To systematically study this perspective, we organize the survey around four connected dimensions. First, we examine the hardware foundation that bounds sensing, computation, feedback delivery, and sustained deployment. Second, we study wearable intelligence, where egocentric signals are transformed into perceptual, contextual, and agentic capabilities. Third, we discuss interaction design, through which users request, receive, correct, and regulate assistance during ongoing activity. Fourth, we analyze application scenarios across healthcare, accessibility, situated learning, daily life assistance, cultural tourism, and industrial support, showing how domain requirements reshape system design and evaluation. We further identify five cross-cutting research challenges for future AI smart glasses: next-generation hardware, trustworthy egocentric intelligence, lifelong personalized memory, proactive intelligence, and embodied foundation models. By centering smart glasses as wearable-intelligence platforms, this survey provides a unified framework for organizing technologies, applications, and open challenges in this emerging area.
