Téléchargez le livre : Robust Subspace Estimation Using Low-Rank Optimization

Robust Subspace Estimation Using Low-Rank Optimization

Theory and Applications

de

,

Éditeur :

Springer


Collection :

The International Series in Video Computing

Paru le : 2014-03-24



eBook Téléchargement , DRM LCP 🛈 DRM Adobe 🛈
Lecture en ligne (streaming)
52,74 €
Téléchargement immédiat
Dès validation de votre commande
Ajouter à ma liste d'envies
Image Louise Reader présentation

Louise Reader

Lisez ce titre sur l'application Louise Reader.

badge apple Application Louise Reader
badge Android Application Louise Reader
Description

Various fundamental applications in computer vision and machine learning require finding the basis of a certain subspace. Examples of such applications include face detection, motion estimation, and activity recognition. An increasing interest has been recently placed on this area as a result of significant advances in the mathematics of matrix rank optimization. Interestingly, robust subspace estimation can be posed as a low-rank optimization problem, which can be solved efficiently using techniques such as the method of Augmented Lagrange Multiplier. In this book, the authors discuss fundamental formulations and extensions for low-rank optimization-based subspace estimation and representation. By minimizing the rank of the matrix containing observations drawn from images, the authors demonstrate  how to solve four fundamental computer vision problems, including video denosing, background subtraction, motion estimation, and activity recognition.
Pages
114 pages
Collection
The International Series in Video Computing
Parution
2014-03-24
Marque
Springer
EAN papier
9783319041834
EAN EPUB
9783319041841
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
11
Taille du fichier
3666 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
52,74 €

Suggestions personnalisées