Robust Subspace Estimation Using Low-Rank Optimization

Name: Robust Subspace Estimation Using Low-Rank Optimization
Brand: Springer International Publishing AG
SKU: 9783319041834
Price: 1147 CZK
Availability: InStock

Autor: Omar Oreifej, Mubarak Shah

Jazyk:

Vazba: Pevná

Vydavatel: Springer International Publishing AG

Dostupnost: Skladem u dodavatele

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Recovering the low-rank structure of a linear subspace using a small set of corrupted examples has r...

Informace o knize

Autor

Omar Oreifej, Mubarak Shah

Jazyk

Angličtina

Vazba

Kniha - Pevná

Vydáno

2014

Stránek

114

EAN

9783319041834

ISBN

3319041835

Enbook ID

02300982

Vydavatel

Springer International Publishing AG

Hmotnost

344

Rozměry

162 x 237 x 13

Kompletní popis

Recovering the low-rank structure of a linear subspace using a small set of corrupted examples has recently been made feasible through substantial advances in the area of matrix completion and nuclear-norm minimization. Such low-rank structures appear in certain conditions heavily in computer vision, for instance, in the frames of a video, the camera motion, and a picture of a building façade. In this book, we discuss several formulations and extensions of low-rank optimization, and demonstrate how recovering the underlying basis and detecting the corresponding outliers allow us to solve fundamental computer vision problems, including video denoising, background subtraction, action detection, and complex event recognition.§

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Robust Subspace Estimation Using Low-Rank Optimization

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