EAGER: Collaborative Research: Augmented 360 Video for Situation Awareness in Firefighting

EAGER:协作研究:用于消防态势感知的增强型 360 度视频

基本信息

项目摘要

Fire incidents have caused substantial injuries, illness, and death on both firefighters and civilians. Poor communications between commanders in the control center and firefighters working at emergency sites are frequently cited as the determining factor in fatality and loss reports of firefighter operations. Traditionally, remote commanders visualize emergency sites and lead the operation using videos captured by helmet cameras of firefighters. Unfortunately, these video systems suffer from a fundamental problem, i.e., commanders are only able to see a single view of the emergency site at a time. This limitation restricts the situation awareness of commanders and leads to productivity and safety issues such as miscommunication of locations and failure to identify dangerous events. This project combines 360-degree videos and augmented reality to enable remote commanders to achieve 360-degree situation awareness of the entire emergency site in all viewing directions and enhance firefighting productivity and safety. The 360-degree video viewing benefits various emergency response communities in planning and training. Other research outcomes, including open datasets and software, are widely disseminated through publications, presentations, and websites to contribute to the computer science and engineering communities. Educational activities including undergraduate research as well as fire safety training for K-12 students are also planned to enhance the impacts of this project. This project will design and develop augmented 360 video technology to enable remote commanders to switch viewports within a 360-degree scene and visualize machine-detected events of interest. It will investigate an augmented 360 video viewing system to enable panoramic situation awareness for incident command in firefighter operations through these steps: (1) to address commanders’ needs and requirements for situation awareness in firefighter videos, interviews will be performed to identify and categorize important objects and events in firefighter response and their technology preferences; (2) to fill in the knowledge gap of how to enable automatic machine detection of important events in firefighter videos, a view of interest detection model will be designed detects target objects and events; and (3) to provide panoramic situation awareness to commanders, an augmented 360 video viewing system for remote incident command will be developed and evaluated through a field study.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.
火灾事故导致消防员和平民大量受伤、患病和死亡。控制中心指挥官和紧急救援现场的消防员之间的沟通不畅经常被认为是消防员行动死亡和损失报告的决定性因素。指挥官使用消防员头盔摄像机拍摄的视频来可视化紧急现场并领导行动。不幸的是,这些视频系统存在一个根本问题,即指挥官一次只能看到紧急现场的单个视图。的态势感知该项目结合了 360 度视频和增强现实技术,使远程指挥员能够在所有观看方向上实现整个应急现场的 360 度态势感知。 360 度视频观看有利于各种应急响应社区的规划和培训,包括开放数据集和软件,通过出版物、演示文稿和网站广泛传播,为计算机做出贡献。还计划开展本科生研究以及针对 K-12 学生的消防安全培训等教育活动,以增强该项目的影响力。该项目将设计和开发增强型 360 度视频技术,使远程指挥官能够在其中切换视口。它将研究增强型 360 度视频观看系统,通过以下步骤实现消防员行动中事件指挥的全景态势感知:(1) 满足指挥官的需求。以及消防员视频中态势感知的要求,将进行访谈以识别和分类消防员响应中的重要对象和事件及其技术偏好(2)填补如何实现消防员重要事件的自动机器检测的知识空白; (3) 为了向指挥官提供全景态势感知,将开发用于远程事件指挥的增强型 360 度视频观看系统,并通过现场研究进行评估。奖项反映通过使用基金会的智力价值和更广泛的影响审查标准进行评估,NSF 的法定使命被认为值得支持。

项目成果

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Klara Nahrstedt其他文献

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  • DOI:
  • 发表时间:
    1999
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Klara Nahrstedt
  • 通讯作者:
    Klara Nahrstedt
Challenges in Metaverse Research: An Internet of Things Perspective
元宇宙研究的挑战:物联网视角
SAVG360: Saliency-aware Viewport-guidance-enabled 360-video Streaming System
SAVG360:支持显着性视口引导的 360 度视频流系统
Performance of detection statistics under collusion attacks on independent multimedia fingerprints
独立多媒体指纹共谋攻击下的检测统计性能
  • DOI:
    10.1109/icme.2003.1220890
  • 发表时间:
    2003-07-06
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Thinh Nguyen;Puneet Mehra;A. Zakhor;Susie Wee;John G. Apostolopoulos;Wai;S. Roy;Jacob Chakareski;Eric Setton;Yi Liang;Bernd Girod;M. Fumagalli;Cefriel;Italy;P. Sagetong;Antonio Ortega;Amy Reibman;V. Vaishampayan;Rémi Ronfard;Tien Tran Thuong;France Inria;Xiaofei He;Adam Berenzweig;Daniel P W Ellis;Tong Zhang;M. Boutell;Yeow Kee Tan;N. Sherkat;Tony Allen;Y. Sawahata;Kiyoharu Aizawa;Timothy T H Chen;Sidney Fels;Sarah Saehee;Min;Xin Fan;China;Xing Xie;Wei;Hong;Björn Schuller;M. Zobl;G. Rigoll;Manfred Lang;Hsuan;Shrikanth S Narayanan;C.;Rongshan Yu;Xiao Lin;S. Rahardja;Simon Lucey;Tsuhan Chen;M. Reyes;Chih;Sau;Yongmin Li;Li;Geoff Morrison;Charles Nightingale;J. Morphett;Jun;John Zhang;Jagath Chen;Samarab;u;u;S. H. Srinivasan;M. Kankanhalli;Wei;Hasan Ates;Andy Chang;Oscar C. Au;Ming Yeung;Hong Kong;Gulcin Caner;Yu Hen Hu;Rajas A. Sambhare;N. Bellas;M. Dwyer;Tay;Chin;Tsung;Yu;Chien;Chen;Hung;C. Jen;Satoshi Nishiguchi;Kazuhide Higashi;Y. Kameda;Tsung;Wen;Chun;Hung;Tu;Yu;Ya;Liang;Jongmyon Kim;Scott Wills;Michelle Yan;J. Shaw;Shinsuke Kobayashi;Kentaro Mita;Yoshinori Takeuchi;Ioannis Andreou;N. Sgouros;Michael Lee;Surya Nepal;Uma Srinivasan;Csiro;Australia;Gees Stein;J. Rittscher;A. Hoogs;H. Nagano;K. Kashino;Hiroshi Murase;Ahmet Ekin;Amit Chakraborty;P. Liu;L. Hsu;Lijun Yin;Sergey Royt;Francis Quek;Yingen Xiong;Haitao Zheng;J. Taal;I. Haratcherev;K. Langendoen;T. Stockhammer;Jie Chen;S. Hsia;Trista Pei;Hong Zhao;Min Wu;Z. J. Wang;K. Liu;A. Giannoula;A. Tefas;N. Nikolaidis;I. Pitas;M. Fu;N. Cvejic;D. Tujkovic;T. Seppänen;Jonathan Foote;John Adcock;Andreas Girgensohn;S. Mallick;Mohan Trivedi;Inmaculada Rodríguez;Manuel Peinado;Cha Zhang;Yuzhong Shen;K. Barner;Yong;Jang;Dae;Jong;Wende Zhang;Thang Viet Nguyen;Ch;ra Patra;ra;Ee;Wei Wang;Aidong Zhang;S. Palanivel;B. Venkatesh;B. Yegnanarayana;Dong;Michael R. Lyu;D. Trossen;Hemant Chaskar;Shengjie Zhao;Zixiang Xiong;A. Bhatkar;R. Ch;ramouli;ramouli;Wen Xu;S. Hemami;Wanghong Yuan;Klara Nahrstedt;Jiancong Chen;S.;Jieh Hsiang;Wen;Bee;Hsieh;J. Assfalg;A. Bimbo;P. Pala;Xiangdong Zhou;Qi Zhang;Jun Gao;G. Tzanetakis;P. Steenkiste;Lei Zhang;Yu;Xin Huang;Shu;Minghong Pi;Mrinal M;al;al;Anup Basu;G. Iyengar;H. Nock;C. Neti;Min Xu;Ling;Chang Xu;Qi Tian;Ching;Shao;Yi;Yu;A. Pinho;Antonio Neves;Nejat Kamaci;Y. Altunbasak;Xiaodong Gu;Microsoft Research;Asia;Yung;Ming;Yu;Martin Boliek;Kok Wu;Shou;Liang Zhang;Yuhua Ding;G. Vachtsevanos;Anthony Yezzi;Wayne Daley;Bonnie Heck;Chuo;P. Ramanathan;Xiaoqing Zhu;Christian Ritz;Ian Burnett;J. Lukasiak;H. Zarrinkoub;Om Deshmukh;Carol Y. Espy;K. S. Rao;Arun Kumar;Xiaodong He;Dong Wang;J. Pinquier;Jean;R. André;France Top;Mohammed Chalil;Sreekumar K P;Manoj Sankar;A. Raouzaiou;K. Karpouzis;S. Kollias;Ghassan Al;Magy Seif El;I. Horswill;Son Tran;Raghavendra Singh;Ravi Kothari;M. Naphade;States Apostol;Paul Natsev;Belle L. Tseng;John R Smith;Shinsuke Nakajima;Apostol;W. Kumwilaisak;Research Asia;Bo Shen;Sheau;Chun;Rajeev Kumar;Nam Pham;Ngoc;K. Leuven;Belgium;G. Lafruit;J. Mignolet;S. Vernalde;G. Deconinck;Rudy Lauwereins;Belgium Top;Pun;Tien;Amit Kale;Roy Chowdhury;Sarah John
  • 通讯作者:
    Sarah John
DARTS: Distributed IoT Architecture for Real-Time, Resilient and AI-Compressed Workflows
DARTS:用于实时、弹性和人工智能压缩工作流程的分布式物联网架构

Klara Nahrstedt的其他文献

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{{ truncateString('Klara Nahrstedt', 18)}}的其他基金

Collaborative Research: Conference: NSF Workshop Sustainable Computing for Sustainability
协作研究:会议:NSF 可持续计算可持续发展研讨会
  • 批准号:
    2334854
  • 财政年份:
    2023
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
CC* Integration-Large: MAINTLET: Advanced Sensory Network Cyber-Infrastructure for Smart Maintenance in Campus Scientific Laboratories
CC* 大型集成:MAINTLET:用于校园科学实验室智能维护的先进传感网络网络基础设施
  • 批准号:
    2126246
  • 财政年份:
    2021
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
Collaborative Research: CNS Core: Medium: miVirtualSeat: Semantics-aware Content Distribution for Immersive Meeting Environments
协作研究:CNS 核心:媒介:miVirtualSeat:用于沉浸式会议环境的语义感知内容分发
  • 批准号:
    2106592
  • 财政年份:
    2021
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
CNS Core: Medium: Collaborative Research: Scalable Dissemination and Navigation of Video 360 Content for Personalized Viewing
CNS 核心:媒介:协作研究:视频 360 内容的可扩展传播和导航以实现个性化观看
  • 批准号:
    1900875
  • 财政年份:
    2019
  • 资助金额:
    $ 15万
  • 项目类别:
    Continuing Grant
CC* Integration: SENSELET: Sensory Network Infrastructure for Scientific Laboratory Environments
CC* 集成:SENSELET:科学实验室环境的传感网络基础设施
  • 批准号:
    1827126
  • 财政年份:
    2018
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
AiTF: Collaborative Research: Algorithms for Smartphone Peer-to-Peer Networks
AiTF:协作研究:智能手机点对点网络算法
  • 批准号:
    1733872
  • 财政年份:
    2017
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
CC*Integration: BRACELET: Robust Cloudlet Infrastructure for Scientific Instruments' Lifetime Connectivity
CC*Integration:BRACELET:用于科学仪器终身连接的强大 Cloudlet 基础设施
  • 批准号:
    1659293
  • 财政年份:
    2017
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
CIF21 DIBBs: T2-C2: Timely and Trusted Curator and Coordinator Data Building Blocks
CIF21 DIBB:T2-C2:及时且值得信赖的策展人和协调员数据构建块
  • 批准号:
    1443013
  • 财政年份:
    2014
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
Security for Cloud Computing - NSF Workshop
云计算安全 - NSF 研讨会
  • 批准号:
    1213373
  • 财政年份:
    2012
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
NetSE: Large: Collaborative Research: Exploiting Multi-Modality for Tele-Immersion
NetSE:大型:协作研究:利用多模态实现远程沉浸
  • 批准号:
    1012194
  • 财政年份:
    2010
  • 资助金额:
    $ 15万
  • 项目类别:
    Continuing Grant

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合作研究:EAGER:设计纳米材料揭示单纳米粒子光电发射间歇性机制
  • 批准号:
    2345582
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  • 批准号:
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EAGER/Collaborative Research: An LLM-Powered Framework for G-Code Comprehension and Retrieval
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  • 批准号:
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Collaborative Research: EAGER: IMPRESS-U: Groundwater Resilience Assessment through iNtegrated Data Exploration for Ukraine (GRANDE-U)
合作研究:EAGER:IMPRESS-U:通过乌克兰综合数据探索进行地下水恢复力评估 (GRANDE-U)
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    2409395
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