Dynamics Of Visual Motion Processing

Dynamics of Visual Motion Processing

Motion processing is an essential piece of the complex brain machinery that allows us to reconstruct the 3D layout of objects in the environment, to break camouflage, to perform scene segmentation, to estimate the ego movement, and to control our action. Although motion perception and its neural basis have been a topic of intensive research and modeling the last two decades, recent experimental evidences have stressed the dynamical aspects of motion integration and segmentation. This book presents the most recent approaches that have changed our view of biological motion processing. These new experimental evidences call for new models emphasizing the collective dynamics of large population of neurons rather than the properties of separate individual filters. Chapters will stress how the dynamics of motion processing can be used as a general approach to understand the brain dynamics itself.

Dynamics of Visual Motion Processing

Dynamic Vision for Perception and Control of Motion

The application of machine vision to autonomous vehicles is an increasingly important area of research with exciting applications in industry, defense, and transportation likely in coming decades. Dynamic Vision for Perception and Control of Motion has been written by the world's leading expert on autonomous road-following vehicles and brings together twenty years of innovation in the field by Professor Dickmanns and his colleagues at the German Armed Forces university in Munich. The book uniquely details an approach to real-time machine vision for the understanding of dynamic scenes, viewed from a moving platform that begins with spatio-temporal representations of motion for hypothesized objects whose parameters are adjusted by well-known prediction error feedback and recursive estimation techniques. A coherent and up-to-date coverage of the subject matter is presented, with the machine vision and control aspects detailed, along with reports on the mission performance the first vehicles using these innovative techniques built at Munich. Pointers to the future development and likely applications of this hugely important field of research are presented. Dynamic Vision for Perception and Control of Motion will be a key reference for technologist working in autonomous vehicles and mobile robotics in general who wish to access the leading research in this field, as well as researchers and students working in machine vision and dynamic control interested in one of the most interesting and promising applications of these techniques.