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Computer Engineering Commons

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University of Central Florida

Sparse representation

Publication Year

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Full-Text Articles in Computer Engineering

Taming Wild Faces: Web-Scale, Open-Universe Face Identification In Still And Video Imagery, Enrique Ortiz Jan 2014

Taming Wild Faces: Web-Scale, Open-Universe Face Identification In Still And Video Imagery, Enrique Ortiz

Electronic Theses and Dissertations

With the increasing pervasiveness of digital cameras, the Internet, and social networking, there is a growing need to catalog and analyze large collections of photos and videos. In this dissertation, we explore unconstrained still-image and video-based face recognition in real-world scenarios, e.g. social photo sharing and movie trailers, where people of interest are recognized and all others are ignored. In such a scenario, we must obtain high precision in recognizing the known identities, while accurately rejecting those of no interest. Recent advancements in face recognition research has seen Sparse Representation-based Classification (SRC) advance to the forefront of competing methods. However, …


Robust Subspace Estimation Using Low-Rank Optimization. Theory And Applications In Scene Reconstruction, Video Denoising, And Activity Recognition., Omar Oreifej Jan 2013

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 …