This paper discusses our work on building a SmartCaveDrone system [1] to function as “Co-Archaeologists” that can map large caves and enter dangerous or hard-to-reach spaces. We present an optimal 3D reconstruction ...
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This paper discusses our work on building a SmartCaveDrone system [1] to function as “Co-Archaeologists” that can map large caves and enter dangerous or hard-to-reach spaces. We present an optimal 3D reconstruction framework that combines both sparse feature matching and dense surface alignment. Sparse feature matching is used for visual odometry and global camera pose optimization after loops are detected, while dense surface alignment is the way of closing large loops and solving surface mismatching problem. We collected data inside Maya caves in Belize, and evaluated different methods applied on this dataset. Our experiments demonstrate that sparse feature-based tracking is robust for steady tracking, while it is effective and critical to close surface loops. After our experiments, we discussed new emerging research problems that can be explored.
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