CAREER: Sensing the World with the Distributed Camera
CAREER: Sensing the World with the Distributed Camera
批准号:
1149393
负责人:
Noah Snavely
金额:
$49.9万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-03-01 至 2018-09-30
中文摘要
我们生活在一个图像无处不在的世界里,指尖上的图像数量似乎以指数级的速度增长。这些图像来自各种各样的来源,包括互联网地图网站、网络摄像头、监控和侦察摄像头,以及世界各地数以百万计的摄影师将数十亿张图像上传到照片分享网站。综上所述,这些照片来源可以被视为构成一个分布式相机,以前所未有的规模捕捉整个世界,并不断记录城市、山脉、建筑、人和事件。这项研究正在创建基本的计算工具,通过使用计算机视觉技术从互联网照片集合中建立的全球3D模型数据库,来“校准”这个分布式相机。重点是从非结构化照片集合中创建更快、更健壮的3D重建算法,以及世界范围的姿势估计技术--仅从图像数据就可以准确地计算出照片是在世界的什么地方拍摄的。这些工具正在产生世界范围内的大型校准图像数据库,这些数据库可以帮助回答科学(例如,查找中央公园的所有可用照片,以便跟踪不同植物的开花时间)和工程(例如,查找特定桥梁的所有照片,以帮助找出它倒塌的原因)中的问题,并对其他领域,包括安全、消费者摄影和多媒体搜索产生影响。这项研究与教育和推广活动紧密结合在一起,并计划为高中生举办一个暑期研讨会,让他们参与3D视觉技术。
英文摘要
We live in a world of ubiquitous imagery, where the number of images at our fingertips is growing at a seemingly exponential rate. These images come from a wide variety of sources, including Internet mapping sites, webcams, surveillance and reconnaissance cameras, and millions of photographers around the world uploading billions and billions of images to photo-sharing websites. Taken together, these sources of photos can be thought of as constituting a distributed camera capturing the entire world at unprecedented scale, and continually documenting its cities, mountains, buildings, people, and events.This research is creating the basic computational tools for "calibrating" this distributed camera, through use of a world-wide database of 3D models built from Internet photo collections using computer vision techniques. The focus is on creating faster, more robust algorithms for 3D reconstruction from unstructured photo collections, as well as techniques for world-scale pose estimation--computing precisely where in the world a photo was taken from image data alone. These tools are yielding large, world-wide databases of calibrated imagery that can help answer questions in science (e.g., finding all available photos of Central Park so as to track flowering times of different plants) and engineering (e.g., finding all of the photos ever taken of a particular bridge to help figure out why it collapsed), and have impact other areas including security, consumer photography, and multimedia search. This research is closely integrated with education and outreach, and includes plans for a summer workshop for high-school students to engage with 3D vision technologies.
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Collaborative Research: RI: Medium: Learning Compositional Implicit Representations for 3D Scene Understanding
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批准号:2211259
-
项目类别:Standard Grant
-
资助金额:$40.0万
-
财政年份:2022
-
负责人:Noah Snavely
-
依托单位:
RI: Small: Understanding and Synthesizing People in 3D Scenes
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批准号:2008313
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项目类别:Standard Grant
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资助金额:$49.86万
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财政年份:2020
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负责人:Noah Snavely
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依托单位:
CGV: Large: Collaborative Research: Analyzing Images Through Time
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批准号:1111534
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项目类别:Standard Grant
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资助金额:$42.37万
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财政年份:2011
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负责人:Noah Snavely
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依托单位:
RI: Medium: Collaborative Research: Reconstructing Cities from Photographs
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批准号:0964027
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项目类别:Continuing Grant
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资助金额:$24.0万
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财政年份:2010
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负责人:Noah Snavely
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依托单位:
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