PnP Algorithm

PnP (Perspective-n-Points) algorithms are a class of methods used to estimate camera pose or 3D structure from 2D-3D point correspondences, finding applications in diverse fields like robotics, computer vision, and image processing. Current research focuses on improving the accuracy, efficiency, and robustness of PnP, including developing differentiable PnP layers for end-to-end learning in deep neural networks and exploring variations tailored to specific constraints like 2D camera motion. These advancements are driving progress in areas such as 6D object pose estimation, image inpainting, and camera calibration, leading to more accurate and reliable solutions for various computer vision and robotics tasks.