Low-Rank Models in Visual Analysis: Theories, Algorithms, and Applications presents the state-of-the-art on low-rank models and their application to visual analysis. It provides insight into the ideas behind the models and their algorithms, giving details of their formulation and deduction. The main applications included are video denoising, background modeling, image alignment and rectification, motion segmentation, image segmentation and image saliency detection. Readers will learn which Low-rank models are highly useful in practice (both linear and nonlinear models), how to solve low-rank models efficiently, and how to apply low-rank models to real problems.
ISBN: | 9780128127315 |
Publication date: | 5th June 2017 |
Author: | Zhouchen (Professor, Key Laboratory of Machine Perception (MOE), School of Electronics Engineering and Computer Science, P Lin |
Publisher: | Academic Press Inc an imprint of Elsevier Science Publishing Co Inc |
Format: | Paperback |
Pagination: | 260 pages |
Series: | Computer Vision and Pattern Recognition |
Genres: |
Computer vision |