Collaborative Research: CIF: Medium: Occlusion and Directional Resolution in Computational Imaging
Collaborative Research: CIF: Medium: Occlusion and Directional Resolution in Computational Imaging
批准号:
1955864
负责人:
William Freeman
金额:
$60.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-07-01 至 2024-06-30
中文摘要
在不用镜子的情况下看街角似乎是一件不可能的事情,而普通相机似乎也帮不上忙。在这个项目中,研究团队将开发系统来处理来自普通摄像机的图像和视频,以构建转角视图,并推断其他隐藏在直视范围内的场景特征,例如在场的人数。该团队还将扩大带有深度传感器的普通摄像头的使用,例如用于自动驾驶汽车和沉浸式游戏的摄像头。能够看到周围的角落,有可能帮助急救人员,提高航行安全。在成像中使用漫反射光的基本困难是来自多个方向的光在可见表面被合并。非视距成像的方法主要依赖于使用昂贵的高分辨率飞行时间(TOF)测量来根据光路的长度分离光路。这个项目不是完全依赖TOF,而是强调利用不透明对象,这些对象在漫反射表面上如何组合光线方面产生限制和变化。研究小组还将开发一个框架来表达超出条件数字的反问题难度,以提供局部和方向性的概念来解决。分析将受到概念验证实验的启发和启发。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。
英文摘要
Seeing around a corner without using a mirror seems like an impossible feat, and an ordinary camera does not seem to help. In this project, the research team will develop systems to process images and videos from ordinary cameras to construct around-the-corner views and to infer other scene features that are hidden from direct view such as the numbers of people present. The team will also augment the use of ordinary cameras with depth sensors such as those used in self-driving cars and immersive gaming. Being able to see around corners has the potential to aid first responders and improve navigation safety. The fundamental difficulty in using diffusely reflected light in imaging is that light from many directions is combined at the visible surface. Methods for non-line-of-sight imaging have predominantly depended on separating light paths by their lengths using expensive, high-resolution time-of-flight (TOF) measurement. Instead of depending entirely on TOF, this project emphasizes the exploitation of opaque objects that create restrictions and variations in how light is combined at a diffuse surface. The research team will also develop a framework to express inverse problem difficulty that goes beyond condition numbers to provide localized and directional concepts for resolution. Analyses will inspire and be informed by proof-of-concept experiments.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.
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会议论文
CompCog: Advancing Understanding of Visual Crowding
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批准号:1826757
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项目类别:Standard Grant
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资助金额:$68.92万
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财政年份:2018
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负责人:William Freeman
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依托单位:
RI: Large: Collaborative Research: Reconstructive recognition: Uniting statistical scene understanding and physics-based visual reasoning
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批准号:1212849
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负责人:William Freeman
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依托单位:
CGV: Large: Collaborative Research: Analyzing Images Through Time
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批准号:1111415
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项目类别:Continuing Grant
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资助金额:$102.88万
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财政年份:2011
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负责人:William Freeman
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依托单位:
Group Travel Grant to 2005 IEEE International Conference on Computer Vision in Beijing, China October 15-21, 2005
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批准号:0529738
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项目类别:Standard Grant
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资助金额:$3.0万
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财政年份:2005
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负责人:William Freeman
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依托单位:
Shared Feature Object Detection
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批准号:0413232
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项目类别:Standard Grant
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资助金额:$34.0万
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财政年份:2004
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负责人:William Freeman
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依托单位:
国内基金
海外基金
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