Incremental Reconstruction

Incremental reconstruction focuses on building 3D models or representations from sequential data, such as images or sensor scans, aiming for efficient and accurate scene representation. Current research emphasizes methods leveraging neural networks (e.g., NeRFs), implicit surface representations (like voxel octrees and distance fields), and efficient triangulation algorithms to handle large datasets and complex trajectories. These advancements improve the speed, memory efficiency, and quality of 3D reconstruction, impacting fields like robotics, computer vision, and medical imaging through applications such as autonomous navigation, virtual reality, and medical image analysis.