Computational Analysis Of Visual Motion

Computational Analysis of Visual Motion

Image motion processing is important to machine vision systems because it can lead to the recovery of 3D structure and motion. Author Amar Mitiche offers a comprehensive mathematical treatment of this key subject in visual systems research. Mitiche examines the interpretation of point correspondences as well as the interpretation of straight line correspondences and optical flow. In addition, the author considers interpretation by knowledge-based systems and presents the relevant mathematical basis for 3D interpretation.

Computer Analysis of Visual Motion and its Applications in Outdoor Environments

Computer Vision Analysis of Image Motion by Variational Methods

This book presents a unified view of image motion analysis under the variational framework. Variational methods, rooted in physics and mechanics, but appearing in many other domains, such as statistics, control, and computer vision, address a problem from an optimization standpoint, i.e., they formulate it as the optimization of an objective function or functional. The methods of image motion analysis described in this book use the calculus of variations to minimize (or maximize) an objective functional which transcribes all of the constraints that characterize the desired motion variables. The book addresses the four core subjects of motion analysis: Motion estimation, detection, tracking, and three-dimensional interpretation. Each topic is covered in a dedicated chapter. The presentation is prefaced by an introductory chapter which discusses the purpose of motion analysis. Further, a chapter is included which gives the basic tools and formulae related to curvature, Euler Lagrange equations, unconstrained descent optimization, and level sets, that the variational image motion processing methods use repeatedly in the book.