Graphical Models for Computer Vision

Ji, Qiang

Graphical Models for Computer Vision

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商品描述

Graphical Models for Computer Vision introduces probabilistic graphical models (PGMs) for computer vision problems and teaches how to develop the PGM model from training data. This book discusses PGMs and their significance in the context of solving computer vision problems, giving the basic concepts, definitions and properties. It also provides a comprehensive introduction to well-established theories for different types of PGMs, including both directed and undirected PGMs, such as Bayesian Networks, Markov Networks and their variants.

 

  • Discusses PGM theories and techniques with computer vision examples
  • Focuses on well-established PGM theories that are accompanied by corresponding pseudocode for computer vision
  • Includes an extensive list of references, online resources and a list of publicly available and commercial software
  • Covers computer vision tasks, including feature extraction and image segmentation, object and facial recognition, human activity recognition, object tracking and 3D reconstruction

商品描述(中文翻譯)

《計算機視覺的圖形模型》介紹了應用於計算機視覺問題的概率圖形模型（PGMs），並教授如何從訓練數據中開發PGM模型。本書討論了PGMs及其在解決計算機視覺問題中的重要性，介紹了基本概念、定義和特性。同時，它還全面介紹了不同類型的PGMs的成熟理論，包括有向和無向PGMs，如貝葉斯網絡、馬爾可夫網絡及其變體。

本書的特點如下：
- 通過計算機視覺示例討論PGM理論和技術
- 重點介紹成熟的PGM理論，並附有相應的計算機視覺偽代碼
- 包含廣泛的參考文獻、在線資源和公開可用及商業軟件列表
- 涵蓋計算機視覺任務，包括特徵提取和圖像分割、物體和人臉識別、人體活動識別、物體跟踪和三維重建。

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