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In-depth resource on outdoor optical flow estimation, delivering tools needed to enhance performance and reliability of systems Clearing the Vision 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
Clearing the Vision include:
- Techniques to empower systems to tackle the complexities of outdoor environments, such as methods to enhance visibility in foggy, rainy, or hazy conditions
- Optical flow estimation techniques including the classic model, improved variational methods, total variation methods, and non-local methods
- Optical flow estimation-based segmentation, the influence of parameters, and quantitative and qualitative evaluation measures
- Current research trends and problems still to be solved in the field
Clearing the Vision 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.
List of contents
About the Authors
- Introduction
- Fundamentals of Optical Flow
- Robust NLTV-L^1 Optical Flow Estimation under Adverse Outdoor Conditions
- Robust Optical Flow Estimation via Edge-Preserving Filter
- Optical Flow Estimation via Weighted Guided Filter with Non-Local Steering Kernel
- Advance Deep Learning Approaches for Optical Flow Estimation
- Optical Flow in Real-Time Systems and Autonomous Vehicles
- Drones and Aerial Surveillance for Optical Flow Estimation in Adverse Outdoor Conditions
- Conclusions and Future Work
Index
About the author
Dr. Sana Rao is a Lecturer at Virtual University of Pakistan, Pakistan. Her research areas are computer vision and motion estimation. She has significant experience collaborating with public and private sector research groups.
Dr. Rao Kashif is an Assistant Professor in the Department of Computer Science and Engineering at NUML, Multan, Pakistan. Prior, he is CEO and Managing Director at the Center to Advance Level Research and Development, LTD, Pakistan.
