Carte Robust Subspace Estimation Using Low-Rank Optimization Omar Oreifej

Robust Subspace Estimation Using Low-Rank Optimization

Limbă: engleză
Legare: Copertă tare
Disponibilitate: În depozitul extern
Expediem în 10-13 zile
277.38 lei
Recovering the low-rank structure of a linear subspace using a small set of corrupted examples has r...

Informații despre carte

Limbă
engleză
Legare
Carte - Copertă tare
Publicat
2014
Pagini
114
EAN
9783319041834
ISBN
3319041835
Enbook ID
02300982
Greutate
344
Dimensiuni
162 x 237 x 13

Descriere completă

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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