Recent advancements in low-cost acquisition technologies have made it more practical to acquire real-world datasets on a large scale. This has led to a number of computer-based solutions for reassembling, archiving and visualizing cultural heritage artifacts.
In this talk, I will show how to combine aspects of these technologies in novel ways, and introduce algorithms that improve upon their overall efficiency and robustness. First, I will introduce a 2D acquisition pipeline that generates higher resolution color and normal maps than those available with the 3D scanning devices typically used in practical settings. Next, I will incorporate these normal maps into a novel multi-cue matching system that uses machine learning to reassemble small fragments of artifacts.
I will show examples of how this system is used by archaeologists at the Akrotiri Excavation Laboratory of Wall Paintings in Santorini Greece for reconstructing the Theran Frescoes. I will then present a non-photorealistic rendering pipeline for illustrating geometrically complex objects using images with multiple channels of information. I will demonstrate how this work is used for visualizing historic artifacts from digital museum collections.
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