3D Computer Vision: Foundations and Advanced Methodologies

This  book offers a comprehensive and unbiased introduction to 3D Computer  Vision, ranging from its foundations and essential principles to  advanced methodologies and technologies. Divided into 11 chapters, it  covers the main workflow of 3D computer vision as follows: camera  imaging and calibration models; various modes and means of 3D image  acquisition; binocular, trinocular and multi-ocular stereo vision  matching techniques; monocular single-image and multi-image scene  restoration methods; point cloud data processing and modeling;  simultaneous location and mapping; generalized image and scene matching;  and understanding spatial-temporal behavior.

Each  topic is addressed in a uniform manner: the dedicated chapter first  covers the essential concepts and basic principles before presenting a  selection of typical, specific methods and practical techniques. In  turn, it introduces readers to the most important recent developments,  especially in the last three years. This approachallows them to quickly  familiarize themselves with the subject, implement the techniques  discussed, and design or improve their own methods for specific  applications. The book can be used as a textbook for graduate courses in  computer science, computer engineering, electrical engineering, data  science, and related subjects. It also offers a valuable reference guide  for researchers and practitioners alike.