Parallel SfM

Parallel Structure from Motion (SfM) aims to efficiently reconstruct 3D models from multiple images by parallelizing the computationally intensive process of feature matching and bundle adjustment. Current research focuses on improving efficiency through techniques like graph-based indexing of global descriptors, detector-free matching methods, and novel algorithms for parallel processing and cluster merging, often leveraging weighted connected dominating sets. These advancements enable faster and more accurate 3D model generation from large-scale datasets, such as those acquired by UAVs, with applications in various fields including structural monitoring, object reconstruction, and robotics. Improved accuracy and robustness, particularly in challenging scenarios like texture-poor scenes and dynamic environments, are also key research goals.