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
About the Author:
GÉRARD MEDIONI chairs the Computer Science Department and is Professor at the Institute for Robotics and Intelligent Systems at the University of Southern California. His research interests include designing and implementing very reliable vision systems to accomplish difficult tasks and establishing bridges between computer vision and computer graphics. SING BING KANG is a member of the Interactive Visual Media Group at Microsoft Research, where he specializes in vision-based modeling. He recently co-edited Panoramic Vision: Sensors, Theory, and Applications, and has served on the technical committees of three major computer vision conferences. He holds 12 US patents.