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.

这个项目是开发新的，有效的距离度量比较两个图像。 这些指标说明了两个影响。 首先，像素可以改变它们的位置，从一个图像变形到另一个图像。 其次，像素可能会改变其强度。 在许多视觉问题中，亮度变化主要是由于照明变化。 研究小组首先解决了照明变化的影响，这使得能够开发一种新的，强大的，鲁棒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和新方法相结合，开发出一种鲁棒的距离，同时考虑图像变形和强度变化。 计算此距离将这两种效果分开，从而提供图像之间的对应关系。 这可以用来跟踪物体相对于光线的运动，匹配在一天中不同时间拍摄的图像，或者识别在不同光线下从不同视角看到的物体，以及它们形状的变化。这个新的度量标准提供了一个计算变形和照明的理论，编码了我们的图像相似性概念。 然而，它仍然是一个相当大的挑战，找到有效地计算这样的图像度量的方法。 因此，研究小组还根据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中的性能，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对现有方法造成了重大挑战。