They start 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 slices Robust regression models fitted using M-estimators, RANSAC, and Hough-based Image change lighting illuminating scenes and objects with real world Content-based image light image capture, includes the question, representation, indexing, searching, learning, and more Face detection, alignment, and recognition - with new solutions to key challenges Perceptual interfaces for integrating vision, speech, and haptic modalities Development with Open Source Computer Vision Library (OpenCV) new SAI framework and patterns for architecting computer vision applications