CCRI: Planning: Establishing A Hand-Gesture Research Platform for Behavior Biometrics and Cognitive Robotics (HGRP)

CCRI：规划：建立行为生物识别和认知机器人（HGRP）手势研究平台

• 批准号: 1925709
• 负责人: Dijiang Huang
• 金额: $ 10万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2021-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1925709&HistoricalAwards=false
• 关键词: CCRI; Planning; Establishing; Hand; Gesture; CCRI; Planning; Establishing; Hand; Gesture

The hand is one of the most complex and beautiful pieces of natural engineering in the human body, and it represents a triumph of complex engineering, exquisitely evolved to perform a range of tasks. Hand-gestures have been used for many areas and how to model hand-gestures has broad and profound impact on addressing the nation's priorities and societal needs, e.g., manipulators and co-robot in manufacturing, natural human-computer interaction for virtual reality, wearable platforms in consumer electronics, hand-gesture biometrics in cybersecurity, etc. In this project, one of the research goals is to build a hand-gesture research platform, Hand-Gesture Research Platform (HGRP). HGRP targets at enabling researchers to easily access various hand-gesture data to validate their hand-gesture recognition models, benchmark the performance of newly developed algorithms, and compare with research outcomes from others. Moreover, HGRP is used to gather research communities' feedback based on existing cutting-edge hand-gesture research to prioritize the need on establishing a hand-gesture focused computing research infrastructure.The HGRP framework is based on a cloud computing platform and is used to enable research capabilities in the following areas: (a) hand-gesture biometrics; (b) cognitive Robotics; and (c) programmable interfaces for gesture-based data processing and visualization. HGRP is composed by the following salient features:*Data collection based on two major types of sensors: (a) motion detection sensors, e.g., wearable sensors such as watch, wrist band, on figure sensors, data motion gloves, infrared motion detection sensors, etc., and (b) video sensors such as leap motion sensors, video recorders, etc. The detected hand-gesture data is sent to data storage for processing and storing. *Data are collected and stored on an objective storage service, and frequently used data is stored in memory storage. *A GPU-based private cloud is established to allow researchers to implement well- known hand-gesture data processing models and establish benchmarking models. HGRP also allows researchers to submit computation tasks for evaluations and comparative studies. HGRP provides a web-based data collection, processing, sharing, and storing APIs that allow researchers remotely to access the hand-gesture repository for data retrieval, processing, sharing, storing through web services APIs.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

手是人体中最复杂，最美丽的天然工程作品之一，它代表了复杂的工程学的胜利，这些胜利旨在执行一系列任务。手势已用于许多领域，以及如何建模手法对满足国家的优先事项和社会需求具有广泛而深远的影响研究平台（HGRP）。 HGRP的目标是使研究人员能够轻松访问各种手持数据，以验证其手势识别模型，基准测试新开发算法的性能，并与其他人的研究成果进行比较。此外，HGRP用于基于现有的尖端手持研究来收集研究社区的反馈，以优先考虑建立手持式注重的计算机研究基础设施的需求。HGRP框架基于云计算平台，用于在以下领域中启用研究能力：（a）手动构思生物测量； （b）认知机器人技术； （c）用于基于手势的数据处理和可视化的可编程接口。 HGRP由以下显着特征组成：*基于两种主要传感器类型的数据收集：（a）运动检测传感器，例如，在图形传感器，数据运动手套，红外运动检测传感器等上，诸如手表，腕带，腕带等可穿戴传感器，以及（b）视频传感器，视频记录器，视频录音器等的储存数据，以发送数据和数据。 *数据收集并存储在目标存储服务上，并且经常使用的数据存储在内存存储中。 *建立了基于GPU的私有云，以使研究人员能够实施知名的手持数据处理模型并建立基准测试模型。 HGRP还允许研究人员提交计算任务以进行评估和比较研究。 HGRP提供了基于Web的数据收集，处理，共享和存储API，使研究人员可以远程访问手持存储库，以进行数据检索，处理，分享，共享，通过Web Services APIS进行存储。该奖项反映了NSF的法定任务，并认为通过基金会的知识优点和广泛的criperia criperia criperia criperia criperia criperia criperia criperia criperia recsection the Appis apis。