Object Detection and Recognition in Digital Images: Theory and Practice (Hardcover)

Boguslaw Cyganek

Object Detection and Recognition in Digital Images: Theory and Practice (Hardcover)
  • 出版商: Wiley
  • 出版日期: 2013-08-05
  • 售價: $5,450
  • 貴賓價: 9.5 折 $5,178
  • 語言: 英文
  • 頁數: 548
  • 裝訂: Hardcover
  • ISBN: 0470976373
  • ISBN-13: 9780470976371

    • 下單後立即進貨 (約1~3週)

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相關主題

商品描述

Object detection, tracking and recognition in images are key problems in computer vision. This book provides the reader with a balanced treatment between the theory and practice of selected methods in these areas to make the book accessible to a range of researchers, engineers, developers and postgraduate students working in computer vision and related fields.

Key features:

  • Explains the main theoretical ideas behind each method (which are augmented with a rigorous mathematical derivation of the formulas), their implementation (in C++) and demonstrated working in real applications.
  • Places an emphasis on tensor and statistical based approaches within object detection and recognition.
  • Provides an overview of image clustering and classification methods which includes subspace and kernel based processing, mean shift and Kalman filter, neural networks, and k-means methods.
  • Contains numerous case study examples of mainly automotive applications.
  • Includes a companion website hosting full C++ implementation, of topics presented in the book as a software library, and an accompanying manual to the software platform.

商品描述(中文翻譯)

物體偵測、追蹤和識別在計算機視覺中是關鍵問題。本書提供讀者在這些領域中選擇方法的理論和實踐之間的平衡處理，以使本書對計算機視覺和相關領域的研究人員、工程師、開發人員和研究生學生具有可讀性。

主要特點：
- 解釋每種方法的主要理論思想（並附有公式的嚴謹數學推導），它們的實現（使用C++）並在實際應用中展示工作。
- 強調基於張量和統計的方法在物體偵測和識別中的應用。
- 提供圖像聚類和分類方法的概述，包括子空間和核心處理、均值漂移和卡爾曼濾波器、神經網絡和k-means方法。
- 包含許多主要是汽車應用的案例研究示例。
- 包含一個附帶的網站，提供本書中所介紹的主題的完整C++實現作為軟件庫，以及相應的軟件平台手冊。

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