基于低成本深度视觉（Kinect）的多用户室内定位系统在灵巧家庭中监测人类活动的特性
Characterization of a Multi-User Indoor Positioning System Based on Low Cost Depth Vision (Kinect) for Monitoring Human Activity in a Smart Home
摘要：
越来越多的系统将室内定位用于许多场景，例如资产跟踪、医疗保健、游戏、制造、物流、购物和安全。许多技术是可用的，并且深度相机的使用变得越来越有吸引力，因为这种设备变得负担得起并且易于处理。本文致力于创建一个基于低成本深度相机（Kinect）的室内定位系统。提出了一种方法来优化深度相机的校准，描述多相机数据融合，并指定一个全球定位投影，以保持与室外定位系统的兼容性。监测人们在家中的活动轨迹是为了及早发现日常活动的变化，这种变化突出了残疾和丧失自主性。该系统旨在改善家庭护理健康管理，以社区可持续的成本更好地结束生命。
英文摘要：
An increasing number of systems use indoor positioning for many scenarios such as asset tracking, health care, games, manufacturing, logistics, shopping, and security. Many technologies are available and the use of depth cameras is becoming more and more attractive as this kind of device becomes affordable and easy to handle. This paper contributes to the effort of creating an indoor positioning system based on low cost depth cameras (Kinect). A method is proposed to optimize the calibration of the depth cameras, to describe the multi-camera data fusion and to specify a global positioning projection to maintain the compatibility with outdoor positioning systems. The monitoring of the people trajectories at home is intended for the early detection of a shift in daily activities which highlights disabilities and loss of autonomy. This system is meant to improve homecare health management at home for a better end of life at a sustainable cost for the community.
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。
