Wiley-IEEE Press Robust Vision for Vision-Based Control of Motion (SPIE/IEEE Series on Imaging Science & Engineering)

Product Description Find the design principles you need to move vision-based control out of the lab and into the real world. In this edited collection of state-of-the-art papers, contributors highly regarded in robust vision bring you the latest applications in the field. Whatever your industry - from space ventures to mobile surveillance - you will discover throughout this comprehensive collection a strong emphasis on robust vision simply unmatched today. You will also gain an in-depth analysis of vision techniques used to control the motion of robots and machines. Expert contributors offer you key insights into: Current control issues including hardware design, system architecture, sensor data fusion, and visual tracking Modeling methods for vision-based sensing Useful summaries of recent conclusions drawn from robust-vision workshops Future research needs If you want to learn today's approaches to robust vision-based control of motion, this extensive collection is a must. Learn from the experts and, in the process, speed your project development and broaden your technical expertise for future collaborative efforts in your industry. From the Inside Flap Find the design principles you need for moving vision-based control out of the lab and into the real world. In this edited collection of state-of-the-art, specially written chapters, contributors highly regarded in robust vision bring you the latest applications in the field. Whatever your industry-from space ventures to mobile surveillance-you will discover throughout this book a strong emphasis on robust vision. You will also find an in-depth analysis of vision techniques used to control the motion of robots and machines. Expert contributors offer insights into: Current control issues including hardware design, system architecture, sensor data fusion, and visual tracking Modeling methods for vision-based sensing Useful summaries of recent conclusions drawn from robust-vision workshops Future research needs Robust Vision for Vision-Based Control of Motion is a valuable tool for learning current approaches to robust vision-based control of motion. Learn from the experts how to speed up your project development and broaden your technical expertise for future collaborative efforts in your industry. From the Back Cover Find the design principles you need for moving vision-based control out of the lab and into the real world. In this edited collection of state-of-the-art, specially written chapters, contributors highly regarded in robust vision bring you the latest applications in the field. Whatever your industry-from space ventures to mobile surveillance-you will discover throughout this book a strong emphasis on robust vision. You will also find an in-depth analysis of vision techniques used to control the motion of robots and machines. Expert contributors offer insights into: Current control issues including hardware design, system architecture, sensor data fusion, and visual tracking Modeling methods for vision-based sensing Useful summaries of recent conclusions drawn from robust-vision workshops Future research needs Robust Vision for Vision-Based Control of Motion is a valuable tool for learning current approaches to robust vision-based control of motion. Learn from the experts how to speed up your project development and broaden your technical expertise for future collaborative efforts in your industry. About the Author Markus Vincze is head of a research group at the Vienna University of Technology, Austria, and leads European research projects. Project RobVision uses vision to navigate a walking robot through the sections of a large container vessel for welding and inspection tasks. His research interests are in the areas of service robotics, robust and reliable visual sensing, and control. Gregory D. Hager is a professor of computer science at Johns Hopkins University. He currently serves as cochairman of the Robotics and Automation Society Technic