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