Reprojiseringsfel

Reprojiseringsfel, or "reprojection error," is a term commonly used in computer vision and photogrammetry to describe inaccuracies that occur during the process of reconstructing a 3D scene from 2D images. It refers to the discrepancy between the observed image points and the projected points obtained from the estimated 3D model. Essentially, reprojection error quantifies how well a computed model aligns with the original image data.

This error arises due to various factors such as noise in the image data, miscalibration of camera parameters, or insufficient image coverage. It is typically measured in pixel units and serves as an indicator of the accuracy of the 3D reconstruction or camera pose estimation. Lower reprojection errors suggest a more precise model, whereas higher errors indicate potential inaccuracies or imperfections in the reconstruction process.

In practical applications, minimizing reprojection error is a primary objective during bundle adjustment, a process used to refine estimates of camera positions and 3D points simultaneously. By iteratively adjusting the parameters to reduce the reprojection error, the accuracy of the model improves, leading to better real-world applications such as 3D mapping, robotic navigation, and augmented reality.

While a certain level of reprojection error is inevitable due to inherent measurement uncertainties, efforts are made to keep this error within acceptable thresholds for specific tasks. Understanding and controlling reprojection error is essential for ensuring the reliability and precision of computer vision systems.