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

手是人体内最复杂、最美丽的自然工程之一，它代表着复杂工程的胜利，经过精心进化，可以执行一系列任务。手势已经被广泛应用于许多领域，如何对手势进行建模对于解决国家的优先事项和社会需求具有广泛而深远的影响，例如制造业中的机械手和协作机器人、虚拟现实中的自然人机交互、消费电子产品中的可穿戴平台、网络安全中的手势生物识别等。本项目的研究目标之一是建立一个手势研究平台--手势研究平台(HGRP)。HGRP的目标是使研究人员能够轻松访问各种手势数据，以验证他们的手势识别模型，对新开发的算法的性能进行基准测试，并与其他研究成果进行比较。此外，HGRP用于收集研究社区基于现有尖端手势研究的反馈，以优先考虑建立以手势为重点的计算研究基础设施的需求。HGRP框架基于云计算平台，用于支持以下领域的研究能力：(A)手势生物识别；(B)认知机器人；(C)基于手势的数据处理和可视化的可编程接口。HGRP由以下两种主要类型的传感器组成：*基于两种主要类型的传感器的数据收集：(A)运动检测传感器，例如可穿戴的传感器，例如手表、腕带、数字传感器、数据运动手套、红外运动检测传感器等；以及(B)视频传感器，例如跳跃运动传感器、录像机等。检测到的手势数据被发送到数据存储器进行处理和存储。*数据收集并存储在目标存储服务上，常用数据存储在内存存储中。*建立基于GPU的私有云，让研究人员实现知名的手势数据处理模型，建立标杆模型。HGRP还允许研究人员提交计算任务以供评估和比较研究。HGRP提供了基于Web的数据收集、处理、共享和存储API，允许研究人员远程访问手势存储库，以通过Web服务API进行数据检索、处理、共享和存储。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.