芸術科学会論文誌 投稿用カバーシート

■ 論文種類
  ・原著論文 フルペーパー    

■ 論文分野
  2) 科学系分野

■ カテゴリ
  a-1) CG技術(モデリング)
  a-4) CG技術(可視化)

■ 該当特集
  ・NICOGRAPH2024 発表論文特集

■ 論文題名
A Study on Automatic Registration of 3D Point Clouds Obtained from Archaeological Trench Investigations

■ 著者名
エンフトゥグス　マラル（学生会員）/ Maral Enkhtugs
游梦博（正会員）/ Mengbo You
太郎良真妃（非会員）/ Maki Tarora
平川ひろみ（非会員）/ Hiromi Hirakawa
中園聡（非会員）/ Satoru Nakazono
今野晃市（正会員）/ Kouichi Konno

■ 著者所属
岩手大学 / Iwate University
岩手大学 / Iwate University
鹿児島国際大学 / The International University of Kagoshima
独立行政法人国立文化財機構 奈良文化財研究所 / Nara National Research Institute for Cultural Properties
鹿児島国際大学/ The International University of Kagoshima
岩手大学 / Iwate University

■ 著者e-mail
g0323212@iwate-u.ac.jp
ymb@iwate-u.ac.jp
taroramaki@gmail.com
hhirakawa001@gmail.com
satorunakazono@yahoo.co.jp
konno21@iwate-u.ac.jp

■ 連絡担当者の氏名、住所、所属、電話、Fax、e-mail
エンフトゥグス　マラル
岩手県盛岡市高松二丁目３５番３３号メープル高松IIＦ１０３号
090-2886-2632
g0323212@iwate-u.ac.jp

■ 論文概要
Traditional archaeological excavations often record only limited details of artifacts and sites, making post-
excavation analysis difficult. A novel approach, consistent 3D excavation, records every detail of the excavation
process by scanning both artifacts and the excavation site to create 3D models. However, the current method
of registering the artifact and site models is entirely manual operation, requiring significant labor and time, and
the result depends heavily on the operator’s skill. This paper proposes a method to automate the registration
of 3D point clouds from an archaeological trench investigation site with individual artifacts (stones) in a
virtual space. The method integrates histogram-based color segmentation and a region-growing algorithm to
extract the topside of stones from the trench point cloud. The segmented stone points are then registered
with the complete stone point cloud, using initial alignments to refine the Iterative Closest Point (ICP)
results, creating a virtual representation of the ruin. To evaluate the effectiveness of the proposed method,
experiments were conducted on two different trench datasets. The results show that the method achieves
high segmentation and registration accuracy, while significantly reducing manual effort and improving efficiency.

■ キーワード
Point cloud
Trench investigation
Shape matching
Registration
Segmentation