Variation methods that are rooted in physics and mechanics, but in many other areas that involve statistics, control, and computer vision, deal with a problem from the optimization standpoint us, d. H. They formulate or as an optimization of an objective function or function. The image motion analysis methods described in this book use variational calculus to minimize (or maximize) an objective function that describes any constraints that characterize the desired motion variables. The book covers the four core topics of motion analysis: motion estimation, recognition, persecution, and three-dimensional interpretation. Each topic is treated in a separate chapter. The presentation will be preceded by an introductory chapter explaining the purpose of motion analysis. In addition, a chapter contains the basic tools and formulas relating to curvature, Euler-Lagrange equations, unlimited descent optimization, and level sets that the various image motion processing methods repeatedly use in the book.