CGV: Small: RUI: Analyzing subspace structure for group level image understanding

今天生成的图像数量的大量增长为计算机视觉研究提供了一个新的方向。今天的图像几乎从来不是独立生成的，而是作为集合显示的。因此，我们现在需要考虑的不是将图像视为单独的实体，而是一个可能具有显著相关结构的群体中的图像。然而，在大多数情况下，一些基本图像分析任务（如图像分割）的形式化仍然是一次只考虑一个图像。这个项目利用这种共享结构来理解图像中的内容。它开发了一个有效的框架，允许在组级别对图像进行分割，因此适用于视觉数据通常呈现的各种场景。主要目标是设计一个全面的系统来解决这个问题的各个方面——从使用训练数据预处理输入，到提供考虑到组结构的强大分割模型，再到构建字典，然后可以用来有效地分割一组相关图像。这个项目为本科生提供了一种工具，让他们在学期和夏季都能全身心地投入到研究中。学生接触并参与计算机视觉的最新研究，这进一步加深了他们对这些主题的理解，激发了他们的求知欲。这可以大大增加这些学生选择在计算机科学领域进行高等学习的可能性。

The massive growth in the number of images being generated today has fostered a new direction in computer vision research. Images today are almost never generated independently, rather manifest as collections. Therefore, instead of thinking of images as individual entities, we now need to consider images within a group that may have significant correlational structure. Yet, formalizations of several fundamental image analysis tasks such as image segmentation, for the most part, still consider one image at a time. This project makes the case for exploiting this shared structure for understanding content in images. It develops an efficient framework which permits the segmentation of images at a group level and therefore is applicable to various scenarios in which visual data typically presents itself. The primary objective is to design a comprehensive system that addresses all aspects of this problem -- from preconditioning the input using training data, to providing powerful segmentation models that take the group structure into account, to building dictionaries which can then be used to effectively segment a set of related images. This project provides a vehicle for engaging undergraduates to become immersed in research during the semesters and full-time in summers. Students are exposed to and participate in state-of-the-art research in computer vision which furthers their understanding of these topics and stimulate their intellectual curiosity. This can significantly increase the possibility of these students choosing to pursue higher studies in computer science.