Extrinsic Camera

Extrinsic camera calibration focuses on determining the spatial relationship between multiple cameras or between a camera and other sensors (e.g., LiDAR, radar). Research emphasizes developing robust and efficient methods for this calibration, often employing deep learning architectures (like those leveraging geometric optimization or cascaded approaches) alongside classical computer vision techniques (e.g., using point-line correspondences or homographies). These advancements are crucial for applications such as 3D reconstruction, autonomous navigation, and multi-sensor data fusion, improving accuracy and reducing the need for laborious manual calibration procedures. The development of targetless and online calibration methods is a significant trend, enabling more flexible and practical deployment in various scenarios.