RI: Small: Exploiting Correlated Sparsity Pattern Change in Dynamic Vision Problems

这个项目开发了一个新的框架来解决一个大类的动态视觉问题，利用相关的稀疏模式变化在适当的域。重点是高维视觉跟踪问题，如变形轮廓跟踪或目标跟踪中存在显着的照明变化。这些是困难的，因为高维度和因为观察模型是高度非线性和/或非高斯由于混乱，闭塞或低对比度。然而，在大多数这样的问题中，即使国家（例如，轮廓变形或照明）是高维的，在任何给定时间，大多数变化仅发生在几个主要方向上。在一个长序列中，这组方向可以随着时间逐渐改变。大多数现有的方法需要一组过去的状态估计来估计这种变化的飞行，同时跟踪噪声或非线性系统。该研究团队将这一难题重新解释为“递归重建具有慢时变稀疏模式的稀疏状态序列”问题，并从他们正在进行的递归稀疏恢复工作中挖掘思路，为这一难题提供了全新的解决方案，该项目的研究丰富了计算机视觉的知识基础，可应用于医学图像分析和视频监控等多种不同的应用领域。该项目通过暑期、高级设计项目和REU项目为研究生提供研究机会，并让本科生参与，包括代表性不足的少数民族。

This project develops a new framework to solve a large class of dynamic vision problems by exploiting correlated sparsity pattern change in the appropriate domain. The focus is on high-dimensional visual tracking problems such as deformable contour tracking or target tracking in the presence of significant illumination changes. These are difficult because of the high dimensionality and because the observation models are highly nonlinear and/or non-Gaussian due to clutter, occlusions or low contrast. However, in most such problems, even though the state (e.g., contour deformation or illumination) is high-dimensional, at any given time, most change occurs in only a few principal directions. In a long sequence, this set of directions can gradually change over time. Most existing methods need a set of past state estimates to estimate this change on-the-fly while tracking noisy or nonlinear systems. The research team provides a completely new solution to this difficult problem by re-interpreting it as a problem of "recursively reconstructing sparse state sequences with slow time-varying sparsity patterns" and tapping into ideas from their ongoing recursive sparse recovery work.The research of this project enriches the knowledge base of computer vision and can be applied to many different applications such as medical image analysis and video surveillance. The project provides research opportunities for graduate students and involves undergraduate students, including under-represented minorities, through summer, senior design projects and REU projects.