人口老龄化是对当今大多数国家的未来产生重大影响的社会因素。为了解决由此而来的巨大经济和社会压力,目前现实可行的方法是依靠高度发展的信息和通信技术,自动识别和理解人们在家居环境下的日常活动(ADL),向老人提供日常生活辅助以尽可能地延长老人在家中独立生活的时间。由于日常生活发生的物理环境是非结构化的自然环境。ADL识别与理解的任务就是动态上下境下,在时间和空间上对用户的日常活动进行观察、处理、分析、推理和决策的过程。这本质上是要求系统具有类似人类的认知能力。因此,ADL的识别和理解是传统的信息处理方法特别是计算机视觉方法、认知计算和推理等基础理论研究,和未来老龄化社会重大应用的交汇点。开展ADL识别与理解的研究将有利于推动学科的发展和社会的进步。本文旨在讨论ADL的识别和理解中的技术挑战和基本科学问题,通过分析相关研究现状以及讨论与ADL识别需求之间的差距,为探索研究思路提供新的方向。

Population aging is a current social factor which impacts significantly on the future of most countries. To relieve such economic and social pressures, one feasible way is to automatically understand the activities of daily living (ADL) of eldly people by using the highly developed information and communication techniques, so as to provide living assistance for eldly people to prolong their independent living time in home. ADL happens under unstructured natural environment. ADL recognition and understanding is actually a process of observation, analysis, inference and decision in space-time domain under dynamic environment. It essentially requires that the computer system should have the human-like cognitive competence. Therefore, ADL recognition and understanding is a confluence of interdisciplinary research (such as computer vision, cognitive computing, and pervasive computing) and real-world applications to cope with the problem of population aging. The goal of this paper is to discuss the challenges and basic scientific problems in ADL recognition and understanding, and to discuss possible future directions to reduce the gap between the start-of-art and requirements of ADL recognition in real world.