Emerging Topics in Computer Vision. Gerard Medioni, Sing Bing Kang

Emerging Topics in Computer Vision



Download Emerging Topics in Computer Vision



Emerging Topics in Computer Vision Gerard Medioni, Sing Bing Kang ebook pdf
Publisher: Prentice Hall PTR
Language: English
Page: 668
ISBN: 0131013661, 9780131013667

The state-of-the art in computer vision: theory, applications, and programming

Whether you're a working engineer, developer, researcher, or student, this is your single authoritative source for today's key computer vision innovations. Gerard Medioni and Sing Bing Kang present advances in computer vision such as camera calibration, multi-view geometry, and face detection, and introduce important new topics such as vision for special effects and the tensor voting framework. They begin with the fundamentals, cover select applications in detail, and introduce two popular approaches to computer vision programming.

Camera calibration using 3D objects, 2D planes, 1D lines, and self-calibration Extracting camera motion and scene structure from image sequences Robust regression for model fitting using M-estimators, RANSAC, and Hough transforms Image-based lighting for illuminating scenes and objects with real-world light images Content-based image retrieval, covering queries, representation, indexing, search, learning, and more Face detection, alignment, and recognition--with new solutions for key challenges Perceptual interfaces for integrating vision, speech, and haptic modalities Development with the Open Source Computer Vision Library (OpenCV) The new SAI framework and patterns for architecting computer vision applications

From the Back Cover

The state-of-the art in computer vision: theory, applications, and programming

Whether you're a working engineer, developer, researcher, or student, this is your single authoritative source for today's key computer vision innovations. Gerard Medioni and Sing Bing Kang present advances in computer vision such as camera calibration, multi-view geometry, and face detection, and introduce important new topics such as vision for special effects and the tensor voting framework. They begin with the fundamentals, cover select applications in detail, and introduce two popular approaches to computer vision programming.

Camera calibration using 3D objects, 2D planes, 1D lines, and self-calibration Extracting camera motion and scene structure from image sequences Robust regression for model fitting using M-estimators, RANSAC, and Hough transforms Image-based lighting for illuminating scenes and objects with real-world light images Content-based image retrieval, covering queries, representation, indexing, search, learning, and more Face detection, alignment, and recognition--with new solutions for key challenges Perceptual interfaces for integrating vision, speech, and haptic modalities Development with the Open Source Computer Vision Library (OpenCV) The new SAI framework and patterns for architecting computer vision applications



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