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II-NEW: Cognitive Sensing Research Infrastructure for Distributed Behavioral Biometrics

II-新：分布式行为生物识别的认知感知研究基础设施

基本信息

批准号：
1059212
负责人：
Fei Hu
金额：
$ 42万
依托单位：
University of Alabama Tuscaloosa
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2011
资助国家：
美国
起止时间：
2011-03-01 至 2015-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1059212&HistoricalAwards=false
关键词：
II NEW Cognitive Sensing Research

项目摘要

Behavioral biometrics, such as gait, walking trajectory, and speech rhythm, are advantageous in their tolerance of low sensory resolution, long sensing distance, and poor environmental conditions. Many applications in security and tele-healthcare require tracking and identification of individuals based on their behavioral traits. Conventional approaches typically use video cameras, which could incur high data throughput and computational costs.This project aims to develop a research infrastructure that enables tracking and identification of individuals? behavioral biometrics through thermal, pressure, photonic, acoustic, fiber-optic, and laser sensors. Besides low cost, those sensors can produce sparse behavioral biometric data that can be analyzed quickly. To achieve this goal, we will develop: (1) a set of tools for novel sampling geometries, cognitive sensing protocols, biometric feature modeling and distributed information aggregation; (2) a multi-agent architecture for system operation and adaptation that enables heterogeneous sensors to achieve consensus in behavior analysis; and (3) a set of programming and evaluation tools for system integration and improvement.The developed computing research infrastructure will enable research activities about behavioral biometrics based on low-cost, low-power, distributed platforms with a variety of sensing modalities. The enabled distributed behavioral biometrics intelligence has great potential to cope with the technical challenges in behavioral biometrics caused by long distances and crowded scenes. The developed education materials will benefit a number of computing and engineering courses for the training of highly skilled workforce on surveillance and security monitoring. The outreach programs include summer student training, faculty workshops, and school visits.

步态、行走轨迹和语音节奏等行为生物特征在其对低传感分辨率、长传感距离和恶劣环境条件的耐受性方面具有优势。安全和远程医疗保健中的许多应用需要基于个人的行为特征来跟踪和识别个人。传统的方法通常使用摄像机，这可能会产生高的数据吞吐量和计算成本。通过热、压力、光子、声学、光纤和激光传感器进行行为生物测定。除了低成本外，这些传感器还可以产生可以快速分析的稀疏行为生物特征数据。为了实现这一目标，我们将开发：（1）一套新的采样几何，认知传感协议，生物特征建模和分布式信息聚合的工具;（2）一个多智能体体系结构的系统操作和适应，使异构传感器实现一致的行为分析;以及（3）一套用于系统集成和改进的编程和评估工具。所开发的计算研究基础设施将使基于低成本、低功耗、具有各种感测模态的分布式平台。已启用的分布式行为生物识别智能具有巨大的潜力，可以科普长距离和拥挤场景所带来的行为生物识别技术挑战。开发的教育材料将有利于一些计算机和工程课程，以培训监视和安全监测方面的高技能劳动力。外展计划包括暑期学生培训，教师研讨会和学校参观。