Camera Intrinsics

Camera intrinsics, the internal parameters describing a camera's optical properties (e.g., focal length, distortion), are crucial for accurate 3D scene reconstruction and computer vision tasks. Current research focuses on estimating these parameters from images, often without relying on traditional calibration methods, employing techniques like self-supervised learning, bundle adjustment, and neural networks (including transformers and convolutional architectures). This work is significant because accurate intrinsic estimation enables advancements in various applications, such as autonomous driving, augmented reality, and robotic vision, by improving the accuracy and robustness of 3D perception systems.