Sub-Image Recapture for Multi-View 3D Reconstruction
This addresses a scalability problem for researchers and practitioners in 3D reconstruction, though it is incremental as it builds on existing algorithms.
The paper tackles the challenge of high memory requirements in 3D reconstruction from large images by introducing a sub-image recapture (SIR) approach that splits images into smaller parts for individual processing, resulting in significantly reduced memory usage and improved scalability.
3D reconstruction of high-resolution target remains a challenge task due to the large memory required from the large input image size. Recently developed learning based algorithms provide promising reconstruction performance than traditional ones, however, they generally require more memory than the traditional algorithms and facing scalability issue. In this paper, we developed a generic approach, sub-image recapture (SIR), to split large image into smaller sub-images and process them individually. As a result of this framework, the existing 3D reconstruction algorithms can be implemented based on sub-image recapture with significantly reduced memory and substantially improved scalability