Optical Flow in Real‐Time Systems and Autonomous Vehicles

This chapter explores the critical role of optical flow in real-time systems and its growing importance in autonomous vehicles. With advancements in sensor technology, machine vision, and real-time data processing, the ability to accurately estimate motion using optical flow algorithms has become fundamental in various real-time applications. These include advanced driver assistance systems (ADAS), robotic navigation, and surveillance systems. Additionally, autonomous vehicles rely heavily on optical flow for scene understanding, obstacle detection, and dynamic path planning. We will delve into the methodologies, challenges, and recent advancements, including the use of deep learning for real-time optical flow, as well as the integration of optical flow in modern vehicular systems.