Stereo Vision System

Stereo vision systems aim to reconstruct three-dimensional scenes from two or more images, mimicking human binocular vision. Current research focuses on improving accuracy and efficiency, particularly through advanced algorithms like those based on recurrent neural networks (e.g., RAFT adaptations) and incorporating diverse camera types (e.g., event cameras and fisheye lenses) to overcome limitations of traditional systems. These advancements are driving progress in robotics (autonomous navigation, remote monitoring), 3D modeling, and other applications requiring precise depth estimation and scene understanding.