Structure From Motion

Structure-from-Motion (SfM) is a computer vision technique that reconstructs 3D scenes and camera poses from multiple 2D images. Current research emphasizes improving robustness and efficiency, particularly in challenging scenarios like those with limited texture or significant motion, often employing hybrid approaches combining point and line features, or leveraging foundation models and neural networks for improved matching and pose estimation. These advancements are crucial for applications ranging from autonomous navigation and 3D modeling to wildlife research and cultural heritage preservation, enabling more accurate and efficient 3D scene understanding from image data.