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A stone chamber is a stone burial facility built inside a mounded tomb (Kofun). A corridor-style stone chamber is a stone chamber built on the side of a Kofun. A corridor-style stone chamber is composed of a main burial chamber for storing a body and a tunnel-shaped passageway to the chamber of a mounded tomb. Many corridorstyle stone chambers have basically the same structure. However, many of stone chambers are different in shapes such as the number of beams in the main burial chamber, and the shapes have been changed after stone on the ceiling is collapsed and sediment is accumulated inside. Archaeologists have been attempting to store and record 3D-measured digital data of stone chambers to protect and manage them1. In [1], a depth sensor in a smartphone is used for 3D measurement, and multiple stone chambers are measured. In addition, the shape similarity between the measured point clouds is visually compared by any 3D CG Viewing software. Meanwhile, the visual comparison is based on subjective and qualitative observation approaches; thus a method for objectively evaluating the similarity is required. A matching method using the scaling iterative closest point (sICP) algorithm is one of the methods for evaluating the similarity between the point clouds. It enables distance minimization of closest point pairs between the point clouds after adjusting the point clouds in a same scale. Then the similarity between the point clouds can be evaluated as this obtained minimum distance. When a corridor-style stone chamber is measured, however, not only the stone chamber in the ground but also the ground surface part will be obtained together as a point cloud. The difference of the ground surface shapes makes shape matching difficult. Owing to the above-mentioned issue, this paper proposes an examination of the stone chamber extraction. It is the base of similarity evaluation between 3D-measured corridor-style stone chambers.
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