Fisheye Video

Fisheye video processing focuses on overcoming the challenges posed by the significant radial distortion inherent in fisheye lenses, aiming to improve the accuracy and efficiency of computer vision tasks applied to this type of wide-field-of-view imagery. Current research emphasizes developing robust rectification methods, often employing deep learning architectures like Vision Transformers and diffusion models, to correct distortions and improve object detection, tracking, and scene understanding. These advancements are crucial for applications such as autonomous driving, traffic monitoring, and surveillance, where fisheye cameras offer a significant advantage in capturing comprehensive visual information.