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CRII: RI: High-Speed Vision-Based Motion Estimation

CRII: RI: High-Speed Vision-Based Motion Estimation
CRII:RI:基于高速视觉的运动估计
批准号:
1464420
负责人:
Jonathan Ventura
金额:
$17.48万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-05-01 至 2020-04-30
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中文摘要
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英文摘要
Device motion estimation is a key component of spatially-aware systems such as mobile robots and virtual or augmented reality displays. Integration of motion estimates over time, or dead reckoning, is typically used to track the position and orientation of the device in space between intermittent absolute position measurements. Vision-based motion estimation is a passive, low-cost approach that provides high accuracy. This project develops faster methods for vision-based motion estimation. The motivation for this work is the basic insight that increasing the speed of motion estimation leads to a "virtuous cycle" of system improvement: by computing the motion estimate more quickly, the camera can be operated a higher rate; this in turns leads to less motion between successive frames, enabling faster computations. The speedups achieved in the current preliminary work rely on two techniques: approximation of the motion model; and reduction of fundamental geometric problem to a smaller form which is quicker to solve. By investigating related problems, the PI seeks to determine an entire class of visual motion estimation problems which can be efficiently solved in a similar way.
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DOI: 10.1109/aivr46125.2019.00018
发表时间: 2019-01
期刊: 2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)
影响因子: --
作者: [Alisha Sharma;Jonathan Ventura]
通讯作者: Alisha Sharma;Jonathan Ventura
CAREER: RUI: CasualVR: Casual Capture of Dynamic Virtual Reality Environments
HDR DSC: Collaborative Research: Central Coast Data Science Partnership: Training a New Generation of Data Scientists
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