Computer Vision: Principles, Algorithms, Applications, Learning, 5/e (Hardcover)

E. R. Davies

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商品描述

Computer Vision: Principles, Algorithms, Applications, Learning (previously entitled Computer and Machine Vision) clearly and systematically presents the basic methodology of computer vision, covering the essential elements of the theory while emphasizing algorithmic and practical design constraints. This fully revised fifth edition has brought in more of the concepts and applications of computer vision, making it a very comprehensive and up-to-date text suitable for undergraduate and graduate students, researchers and R&D engineers working in this vibrant subject.

See an interview with the author explaining his approach to teaching and learning computer vision - http://scitechconnect.elsevier.com/computer-vision/

  • Three new chapters on Machine Learning emphasise the way the subject has been developing; Two chapters cover Basic Classification Concepts and Probabilistic Models; and the The third covers the principles of Deep Learning Networks and shows their impact on computer vision, reflected in a new chapter Face Detection and Recognition.
  • A new chapter on Object Segmentation and Shape Models reflects the methodology of machine learning and gives practical demonstrations of its application.
  • In-depth discussions have been included on geometric transformations, the EM algorithm, boosting, semantic segmentation, face frontalisation, RNNs and other key topics.
  • Examples and applications―including the location of biscuits, foreign bodies, faces, eyes, road lanes, surveillance, vehicles and pedestrians―give the ‘ins and outs’ of developing real-world vision systems, showing the realities of practical implementation.
  • Necessary mathematics and essential theory are made approachable by careful explanations and well-illustrated examples.
  • The ‘recent developments’ sections included in each chapter aim to bring students and practitioners up to date with this fast-moving subject.
  • Tailored programming examples―code, methods, illustrations, tasks, hints and solutions (mainly involving MATLAB and C++)

商品描述(中文翻譯)

《計算機視覺:原理、算法、應用、學習》(前稱《計算機與機器視覺》)清晰而系統地介紹了計算機視覺的基本方法論,涵蓋了理論的基本要素,同時強調算法和實際設計限制。這本全面修訂的第五版增加了更多計算機視覺的概念和應用,使其成為一本非常全面且最新的教材,適合本科生、研究生、研究人員和在這一活躍領域工作的研發工程師閱讀。

請參閱作者的訪談,解釋他對教授和學習計算機視覺的方法 - http://scitechconnect.elsevier.com/computer-vision/


  • 三個新章節關於機器學習強調了這一主題的發展方式;兩個章節涵蓋了基本分類概念概率模型;第三個章節涵蓋了深度學習網絡的原理,並展示了它們對計算機視覺的影響,反映在一個新的章節人臉檢測和識別中。

  • 一個新的章節關於物體分割和形狀模型反映了機器學習的方法論,並實際演示了其應用。

  • 深入討論了幾何變換、EM算法、增強學習、語義分割、人臉正視化、RNN等關鍵主題。

  • 例子和應用包括餅乾、異物、人臉、眼睛、道路車道、監控、車輛和行人的定位,展示了開發實際視覺系統的實際情況。

  • 通過仔細的解釋和豐富的示例,使必要的數學和基本理論易於理解。

  • 每章中的“最新發展”部分旨在使學生和從業人員了解這個快速發展的領域的最新進展。

  • 量身定制的編程示例 - 代碼、方法、插圖、任務、提示和解決方案(主要涉及MATLAB和C++)