RI:Small:Robust Image Matching with Deformations and Lighting Variation

RI：小：具有变形和光照变化的鲁棒图像匹配

• 批准号: 0915977
• 负责人: David Jacobs
• 金额: $ 21.87万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0915977&HistoricalAwards=false
• 关键词: RI; Small; Robust; Image; Matching

This project is to develop new, effective distance metrics for comparing two images. These metrics account for two effects. First, pixels can change their position, deforming from one image to another. Second, pixels may change their intensity. In many vision problems, intensity changes are primarily due to lighting variation. The research team first addresses the effect of illumination changes, which enables to develop a new, powerful, robust distance for measuring the effects of lighting variation in an image. The research team combines this with both existing and new methods to develop a robust distance that accounts simultaneously for image deformations and intensity variations. Computing this distance separates these two effects, providing a correspondence between images. This can be used to track objects moving relative to a light, to match images taken at different times of day, or to recognize objects seen under different lighting, from different viewpoints, with variations in their shape.This new metric provides a theory of computation for deformation and lighting that encodes our notion of image similarity. However, it is still a considerable challenge to find ways to effectively compute with such an image metric. Therefore, the research team also develops computationally effective algorithms based on this new metric. These algorithms improve performance in numerous applications such as face recognition, autonomous navigation, and optical flow and tracking, in which variations in lighting and shape cause significant challenges for existing methods.

该项目旨在开发新的有效距离度量来比较两个图像。 这些指标有两个影响。 首先，像素可以改变它们的位置，从一张图像变形到另一张图像。 其次，像素可能会改变它们的强度。 在许多视力问题中，强度变化主要是由于照明变化造成的。 研究团队首先解决了照明变化的影响，从而能够开发出一种新的、强大的、稳健的距离来测量图像中照明变化的影响。 研究团队将其与现有方法和新方法相结合，开发出一种稳健的距离，可以同时考虑图像变形和强度变化。 计算这个距离可以将这两种效果分开，从而提供图像之间的对应关系。 这可以用来跟踪相对于光移动的物体，匹配在一天中不同时间拍摄的图像，或者识别在不同照明下、从不同角度看到的物体及其形状的变化。这个新的度量提供了一种计算理论用于编码我们的图像相似性概念的变形和照明。 然而，找到有效计算此类图像度量的方法仍然是一个相当大的挑战。 因此，研究团队还基于这一新指标开发了计算有效的算法。 这些算法提高了许多应用的性能，例如人脸识别、自主导航以及光流和跟踪，其中照明和形状的变化给现有方法带来了重大挑战。