Inference and Model Building for Vision-based Estimation of Transmissive Objects

基于视觉的透射物体估计的推理和模型构建

• 批准号: RGPIN-2017-05638
• 负责人: Brubaker, Marcus
• 金额: $ 2.84万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=634341
• 关键词: Inference; Model; Building; Vision; based

This proposal seeks to further the state of the art in the field of computer vision and image processing, with the goal of expanding and reinforcing the use of imaging modalities in our understanding of the world. Images are a rich source of information which are readily captured in many scenarios. The ability to process these images and extract meaning from them is the key goal of computer vision. The long-term objective of this proposal and the PI’s research program in general is the theoretical and practical development of models which enable the estimation of properties of the world from images. One such problem is the estimation of detailed 3D structure of transmissive objects. Imaging and reconstruction of such objects arises in a range of domains including: optical imaging of translucent objects like clouds, glass, water or smoke, x-ray imaging of humans and animals for medical purposes, and transmission electron imaging or materials and biological specimens.

该提案旨在进一步发展计算机视觉和图像处理领域的最新技术，其目标是扩大和加强成像模式在我们理解世界中的使用。图像是丰富的信息源，在许多场景中都很容易捕获。处理这些图像并从中提取含义的能力是计算机视觉的关键目标。该提案和 PI 总体研究计划的长期目标是模型的理论和实践开发，从而能够从图像中估计世界的属性。其中一个问题是透射物体的详细 3D 结构的估计。此类物体的成像和重建出现在一系列领域，包括：云、玻璃、水或烟雾等半透明物体的光学成像，用于医疗目的的人类和动物的 X 射线成像，以及材料和生物样本的透射电子成像。