Dense Image Correspondences for Computer Vision

• Corporate Author: SpringerLink (Online service)
• Other Authors: Hassner, Tal (Editor), Liu, Ce (Editor)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2016.
• Edition: 1st ed. 2016.
• Subjects: Engineering.; Artificial intelligence.; Image processing.; Electrical engineering.; Signal, Image and Speech Processing.; Image Processing and Computer Vision.; Artificial Intelligence (incl. Robotics).; Communications Engineering, Networks.

This book describes the fundamental building-block of many new computer vision systems: dense and robust correspondence estimation. Dense correspondence estimation techniques are now successfully being used to solve a wide range of computer vision problems, very different from the traditional applic...