3D Model Recognition from Stereoscopic Cues provides a rich, integrated account of work done within a large-scale, multisite, Alvey-funded collaborative project in computer vision. It presents a variety of methods for deriving surface descriptions from stereoscopic data and for matching those descriptions to three-dimensional models for the purposes of object recognition, vision verification, autonomous vehicle guidance, and robot workstation guidance. State of the art vision systems are. described in sufficient detail to allow researchers to replicate the results.
Partial Contents: The PMF Stereo Algorithm Project. A Dynamic Programming Algorithm for Binocular Stereo Vision. Stereo Matching Using Intra- and Inter-Row Dynamic Programming. A Computational Theory of Stereo Vision. A Piplid Architecture for the Canny Edge Detector. Estimation of Stereo and Motion Parameters Using a Variational Principle. The 2.5D Sketch Project. Segmentation and Description of Binocularly Viewed Contours. Inferring Surface Shape by Specular Stereo. Surface Descriptions from Stereo and Shading. The 3D Model-Based Vision Project. Matching Geometrical Descriptions in ThreeSpace. Advances in 3D Model Indentification from Stereo Data. Dupin's Cyclide and the Cyclide Patch. Geometric Reasoning in a Parallel Network. SMS: A Suggestive Modelling System for Object Recognition. WPFM: The Workspace Prediction and Fast Matching System. The Design of the IMAGINE II Scene Analysis Program. Overview. TINA: A 3D Vision System for Pick and Place.
|Series:||Artificial Intelligence Series|
|Product dimensions:||8.79(w) x 11.36(h) x 0.89(d)|
About the Author
John P. Frisby is Emeritus Professor of Psychology at the University of Sheffield.