OpenCV 4 with Python Blueprints, Second Edition

Gevorgyan, Menua, Mamikonyan, Arsen, Beyeler, Michael

OpenCV 4 with Python Blueprints, Second Edition

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商品描述

OpenCV is a native cross-platform C++ library for computer vision, machine learning, and image processing. It is increasingly being adopted in Python for development. This book will get you hands-on with a wide range of intermediate to advanced projects using the latest version of the framework and language, OpenCV 4 and Python 3.8, instead of only covering the core concepts of OpenCV in theoretical lessons. This updated second edition will guide you through working on independent hands-on projects that focus on essential OpenCV concepts such as image processing, object detection, image manipulation, object tracking, and 3D scene reconstruction, in addition to statistical learning and neural networks.

You’ll begin with concepts such as image filters, Kinect depth sensor, and feature matching. As you advance, you’ll not only get hands-on with reconstructing and visualizing a scene in 3D but also learn to track visually salient objects. The book will help you further build on your skills by demonstrating how to recognize traffic signs and emotions on faces. Later, you’ll understand how to align images, and detect and track objects using neural networks.

By the end of this OpenCV Python book, you’ll have gained hands-on experience and become proficient at developing advanced computer vision apps according to specific business needs.

商品描述(中文翻譯)

OpenCV 是一個原生跨平台的 C++ 函式庫，用於計算機視覺、機器學習和影像處理。它在 Python 開發中越來越受到採用。本書將讓您親身體驗使用最新版本的框架和語言 OpenCV 4 和 Python 3.8 進行各種中高級項目的實作，而不僅僅是理論課程中涵蓋 OpenCV 核心概念。這本更新的第二版將引導您進行獨立的實作項目，重點關注基本的 OpenCV 概念，如影像處理、物體檢測、影像操作、物體追蹤和 3D 場景重建，以及統計學習和神經網絡。

您將從影像濾鏡、Kinect 深度感應器和特徵匹配等概念開始。隨著進一步的學習，您不僅會親身體驗在 3D 中重建和可視化場景，還會學習如何追蹤視覺上顯著的物體。本書還將通過示範如何識別交通標誌和臉部情緒，幫助您進一步提升技能。隨後，您將了解如何對齊影像，並使用神經網絡檢測和追蹤物體。

通過閱讀本書，您將獲得實踐經驗，並能夠根據特定業務需求開發高級計算機視覺應用程式。

作者簡介

Dr. Menua Gevorgyan

Dr. Menua Gevorgyan is an experienced researcher with a demonstrated history of working in the information technology and services industry. He is skilled in computer vision, deep learning, machine learning, and data science as well as having a lot of experience with OpenCV and Python programming. He is interested in machine perception and machine understanding problems, and wonders if it is possible to make a machine perceive the world as a human does.

Arsen Mamikonyan

Arsen Mamikonyan is an experienced machine learning specialist with demonstrated work experience in Silicon Valley and London, and teaching experience at the American University of Armenia. He is skilled in applied machine learning and data science and has built real-life applications using Python and OpenCV, among others. He holds a master's degree in engineering (MEng) with a concentration on artificial intelligence from the Massachusetts Institute of Technology.

Michael Beyeler

Michael Beyeler is a postdoctoral fellow in neuroengineering and data science at the University of Washington, where he is working on computational models of bionic vision in order to improve the perceptual experience of blind patients implanted with a retinal prosthesis (bionic eye). His work lies at the intersection of neuroscience, computer engineering, computer vision, and machine learning. He is also an active contributor to several open source software projects, and has professional programming experience in Python, C/C++, CUDA, MATLAB, and Android. Michael received a PhD in computer science from the University of California, Irvine, and an MSc in biomedical engineering and a BSc in electrical engineering from ETH Zurich, Switzerland.

作者簡介(中文翻譯)

Dr. Menua Gevorgyan

Dr. Menua Gevorgyan是一位在資訊科技和服務業有豐富經驗的研究員。他擅長於計算機視覺、深度學習、機器學習和數據科學，並且在OpenCV和Python編程方面有豐富的經驗。他對機器感知和機器理解問題感興趣，並且想知道是否有可能使機器像人類一樣感知世界。

Arsen Mamikonyan

Arsen Mamikonyan是一位在矽谷和倫敦有豐富工作經驗的機器學習專家，並在亞美尼亞美國大學有教學經驗。他擅長應用機器學習和數據科學，並使用Python和OpenCV等工具開發了實際應用。他擁有麻省理工學院的工程碩士學位，專攻人工智慧。

Michael Beyeler

Michael Beyeler是華盛頓大學的神經工程和數據科學博士後研究員，他致力於改善植入視網膜假體（仿生眼）的盲人患者的知覺體驗，並開展了仿生視覺的計算模型研究。他的工作涉及神經科學、計算機工程、計算機視覺和機器學習等領域。他還是幾個開源軟件項目的活躍貢獻者，並且在Python、C/C++、CUDA、MATLAB和Android等方面具有專業的編程經驗。Michael在加州大學爾灣分校獲得計算機科學博士學位，並在瑞士蘇黎世聯邦理工學院獲得生物醫學工程碩士學位和電氣工程學士學位。

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