Bundle Adjustment in Computer Vision

Bundle adjustment is a process in computer vision that refines the 3D reconstruction of a scene and the camera positions by jointly optimizing their parameters to best fit the observed images. Think of it as fine-tuning a 3D map created from multiple photos, where initial estimates are improved to reduce error and produce more accurate spatial details. It minimizes discrepancies between the predicted image points and actual observations across all images, ensuring the overall structure and camera placements are consistent, resulting in clearer, more precise 3D models used in applications like robotics, mapping, and augmented reality.