Sparse Bundle Adjustment

Sparse Bundle Adjustment is an optimization process used in computer vision to improve 3D reconstructions from multiple images. It fine-tunes the positions of camera viewpoints and the 3D points they observe, based on the image data, to achieve the most accurate model. The “sparse” aspect refers to efficiently handling large datasets by focusing only on relevant points and camera parameters, reducing computation complexity. Essentially, it systematically adjusts and refines the structure and camera parameters simultaneously, leading to more precise 3D maps, crucial for applications like autonomous navigation, mapping, and photogrammetry.