Computer Engineering Commons^™

Robust Subspace Estimation Using Low-Rank Optimization. Theory And Applications In Scene Reconstruction, Video Denoising, And Activity Recognition., Omar Oreifej

Electronic Theses and Dissertations

In this dissertation, we discuss the problem of robust linear subspace estimation using low-rank optimization and propose three formulations of it. We demonstrate how these formulations can be used to solve fundamental computer vision problems, and provide superior performance in terms of accuracy and running time. Consider a set of observations extracted from images (such as pixel gray values, local features, trajectories . . . etc). If the assumption that these observations are drawn from a liner subspace (or can be linearly approximated) is valid, then the goal is to represent each observation as a linear combination of a compact …