Robust Optical Flow Estimation in Outdoor Environments
Robust Optical Flow Estimation in Outdoor Environments
Hardback
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Sign in or Sign up!- Release Date: 23/01/2026
- Barcode: 9781394294220
- Imprint: Wiley
- Publisher: John Wiley & Sons

Robust Optical Flow Estimation in Outdoor Environments
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DESCRIPTION
In-depth resource on outdoor optical flow estimation, delivering tools needed to enhance performance and reliability of systems Robust Optical Flow Estimation in Outdoor Environments delivers a robust treatment of optical flow estimation under adverse outdoor conditions, offering a comprehensive guide and reference for readers developing vision-based systems that operate in outdoor environments where conditions are unpredictable, varied, and challenging. This book analyzes advanced techniques and strategies for optical flow estimation that enhance the performance and reliability of real-world systems. It outlines everything from the fundamental principles of how objects move within complicated outdoor scenes, such as cars on a road or pedestrians in a park, to specific outdoor environment challenges, including sudden lighting changes and bad weather. The latest advancements in the field are explored, ensuring readers are equipped with the most up-to-date methods for their projects, and a visual roadmap is provided through detailed illustrations that enables readers to grasp even the most complex concepts with ease. Throughout, insightful examples showcasing how this technology is applied in real-life scenarios are offered. Whether it’s improving the safety of self-driving cars or improving the efficiency of surveillance systems, these examples demonstrate the practical impact of the concepts discussed. Sample topics discussed in Robust Optical Flow Estimation in Outdoor Environments include: Robust Optical Flow Estimation in Outdoor Environments is an essential read for researchers in computer vision and robotics and engineers developing autonomous systems and smart surveillance systems. The book is also an excellent supplementary learning resource for courses on computer science, robotics, and autonomous systems.
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