计算机科学
拼图
马赛克
片段(逻辑)
事件(粒子物理)
任务(项目管理)
点(几何)
人工智能
修补
计算机图形学(图像)
软件
计算机视觉
算法
图像(数学)
程序设计语言
数学
考古
物理
几何学
数学教育
历史
经济
管理
量子力学
作者
Daniel Riccio,Sonia Caggiano,Maria De Marsico,Riccardo Distasi,Michele Nappi
标识
DOI:10.1016/j.jvlc.2015.10.010
摘要
When a piece of art from the past is found, it is often broken into several fragments. This is a very common case with frescoes and pottery. Reconstruction from these fragments requires human expertize and it is almost always very hard, if not impossible, to be completely automated. Actually, the problem is an example of jigsaw puzzle solving, which is known to be NP-complete from a computational point of view. The possible high number of fragments and their possible fragility make the task formidable. This work describes software tools that help in two ways. First, reconstruction is assisted by a content-based database of the available pieces. Once acquired by suitable photo equipment and suitably annotated, the fragments can be left untouched and manipulated virtually to find out the best combination before proceeding with the actual reconstruction, if called for. Second, the unavoidable gaps and cracks in the reconstruction are filled by an inpainting module. The results have been assessed by running the system on both artificial datasets and actual case studies.
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