面向密集泛在媒体动态管理的可穿戴传感技术

M. Laibowitz, Nan-Wei Gong, J. Paradiso
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引用次数: 17

摘要

大多数关于无处不在的计算的设想都预测了一个充斥着密集采样传感器的世界,其中许多传感器将能够捕获、分析和传输与个人相关的、潜在的隐私敏感媒体,如视频、音频和识别信息。本文描述了我们设计的一组传感器平台,用于在这种密集的媒体捕获环境中进行个性化、交互和控制实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wearable Sensing for Dynamic Management of Dense Ubiquitous Media
Most visions of ubiquitous computing anticipate a world permeated by a dense sampling of sensors, many of which will be capable of capturing, analyzing, and transmitting personally relevant and potentially privacy-sensitive media, such as video, audio, and identification information. This paper describes a set of sensor platforms that we have designed to experiment with personalization, interaction, and control in such dense media capture environments.
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