Management and Processing of Continuous Streams from Moving Sensors

这个项目的目标是研究一个框架，以捕捉语义和本质的活动有关的移动传感器数据流。 移动传感器是指一类新兴的数据密集型应用，影响学科，如通信，医疗保健，科学应用等，这些应用包括固定数量的传感器，移动和产生数据流作为时间的函数。 例如，在交流方面，听力受损的人可能会使用一种网络手套，将手势翻译成书面（口头）单词。该手套由每个手指关节的传感器组成，该传感器报告其位置作为时间的函数，产生数据流。该框架消耗数据流，并在不同的抽象层次上构建其多级时空表示。 这种多层设计确保了可扩展性、模块化和物理数据独立于流生成设备。虽然这个框架是在几个应用程序的上下文中演示的，但其关键演示是使用虚拟现实手套识别手势（特别是美国手语）的应用程序。 这显示了框架识别新标志的可扩展性及其处理新输入设备的模块性。该框架通过（a）采用用于延迟决策的缓冲器，（B）不同层保持上下文以在输入数据有噪声时提供提示，以及（c）采用极限包络（EoL）的概念以补偿用户在执行时空符号时的轻微变化来提高检测到的模式的质量。可从项目网站（http：//www.example.com）和（infolab.usc.edu）获得更多信息。dblab.usc.edu该项目的更广泛影响是通过将手势作为一种新的信息传递方式与残疾人的应用相结合，进一步推动多媒体领域。

The goal of this project is to investigate a framework to capture both the semantics and essence of an activity pertaining to moving sensor data streams. Moving sensors refers to an emerging class of data intensive applications that impacts disciplines such as communication, health-care, scientific applications, etc. These applications consist of a fixed number of sensors that move and produce streams of data as a function of time. With communication, for example, a hearing impaired individual might utilize a cyber glove that translates hand signs into written (spoken) words. The glove consists of a sensor for each finger joint that reports its location as a function of time, producing streams of data.The framework consumes streams of data and constructs their multi level, spatio temporal representation at different levels of abstraction. This multi-layer design ensures extensibility, modularity, and physical data independence from the stream producing devices. While this framework is demonstrated in the context of several applications, its key demonstration is with an application to recognize hand signs (in particular, American Sign Language) using a virtual-reality glove. This shows the extensibility of the framework to recognize new signs and its modularity to handle new input devices. The framework improves the quality of detected patterns by (a) employing buffers for delayed decision making, (b) different layers maintain context to provide hints when input data is noisy, and (c) employs the concept of Envelope of Limits (EoL) to compensate for a user's slight variations when performing a spatio-temporal sign. More information can be obtained from the project web sites (http://dblab.usc.edu) and (http://infolab.usc.edu). The broader impact of this project is to further the field of multimedia by incorporating hand-gesture as a new mode for conveying information, with applications for the people with disabilities.