Low-Rank Models in Visual Analysis: Theories, Algorithms, and Applications (Computer Vision and Pattern Recognition)

Zhouchen Lin, Hongyang Zhang

Low-Rank Models in Visual Analysis: Theories, Algorithms, and Applications (Computer Vision and Pattern Recognition)

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商品描述

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.

  • Presents a self-contained, up-to-date introduction that covers underlying theory, algorithms and the state-of-the-art in current applications
  • Provides a full and clear explanation of the theory behind the models
  • Includes detailed proofs in the appendices

商品描述(中文翻譯)

《視覺分析中的低秩模型：理論、演算法和應用》介紹了低秩模型及其在視覺分析中的應用的最新研究成果。本書深入探討了這些模型及其演算法背後的思想，詳細介紹了它們的公式和推導過程。主要應用包括視頻降噪、背景建模、圖像對齊和校正、運動分割、圖像分割和圖像显著性檢測。讀者將學習到哪些低秩模型在實踐中非常有用（包括線性和非線性模型），如何高效地解決低秩模型問題，以及如何將低秩模型應用於實際問題。

本書特點如下：
- 提供了一個自成體系、最新的介紹，涵蓋了底層理論、演算法和當前應用的最新研究成果。
- 對模型背後的理論進行了全面清晰的解釋。
- 附錄中提供了詳細的證明。

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