Perspective-n-Point

Perspective-n-Point[1] is the problem of estimating the pose of a calibrated camera given a set of n 3D points in the world and their corresponding 2D projections in the image. The camera pose consists of 6 degrees-of-freedom (DOF) which are made up of the rotation (roll, pitch, and yaw) and 3D translation of the camera with respect to the world. This problem originates from camera calibration and has many applications in computer vision and other areas, including 3D pose estimation, robotics and augmented reality.[2] A commonly used solution to the problem exists for n = 3 called P3P, and many solutions are available for the general case of n ≥ 3. A solution for n = 2 exists if feature orientations are available at the two points.[3] Implementations of these solutions are also available in open source software.

  1. ^ Fischler, M. A.; Bolles, R. C. (1981). "Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography". Communications of the ACM. 24 (6): 381–395. doi:10.1145/358669.358692. S2CID 972888.
  2. ^ Apple, ARKIT team (2018). "Understanding ARKit Tracking and Detection". WWDC.
  3. ^ Fabbri, Ricardo; Giblin, Peter; Kimia, Benjamin (2012). "Camera Pose Estimation Using First-Order Curve Differential Geometry". Computer Vision – ECCV 2012 (PDF). Lecture Notes in Computer Science. Vol. 7575. pp. 231–244. doi:10.1007/978-3-642-33765-9_17. ISBN 978-3-642-33764-2. S2CID 15402824.