TY - GEN
T1 - Manual Preliminary Coarse Alignment of 3D Point Clouds in Virtual Reality
AU - Zhang, Xiaotian
AU - He, Weiping
AU - Wang, Shuxia
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - The alignment of 3D point clouds consists of coarse alignment and precise alignment. The preliminary coarse alignment must be implemented for point clouds with a significant initial pose difference before time-consuming precise alignment. However, this procedure is normally finished on 2D interfaces manually, which leads to a partial perception of the 3D point clouds. The biased understanding may affect the operation efficiency and alignment accuracy. In this paper, we developed a VR-based prototype for manual preliminary coarse alignment of point clouds. A user study was conducted to compare the efficiency, accuracy, and usability in a controlled alignment task with both the 2D interface and the developed system. The task was graded into three levels based on the complexity of matched points clouds (simple, complex, and incomplete). The result indicated that the prototype system was effective and useful for supporting the preliminary coarse alignment task. It displayed outstanding performance for the coarse alignment of complex and incomplete point clouds.
AB - The alignment of 3D point clouds consists of coarse alignment and precise alignment. The preliminary coarse alignment must be implemented for point clouds with a significant initial pose difference before time-consuming precise alignment. However, this procedure is normally finished on 2D interfaces manually, which leads to a partial perception of the 3D point clouds. The biased understanding may affect the operation efficiency and alignment accuracy. In this paper, we developed a VR-based prototype for manual preliminary coarse alignment of point clouds. A user study was conducted to compare the efficiency, accuracy, and usability in a controlled alignment task with both the 2D interface and the developed system. The task was graded into three levels based on the complexity of matched points clouds (simple, complex, and incomplete). The result indicated that the prototype system was effective and useful for supporting the preliminary coarse alignment task. It displayed outstanding performance for the coarse alignment of complex and incomplete point clouds.
KW - Point cloud alignment
KW - Virtual reality
UR - http://www.scopus.com/inward/record.url?scp=85119873966&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-90176-9_55
DO - 10.1007/978-3-030-90176-9_55
M3 - 会议稿件
AN - SCOPUS:85119873966
SN - 9783030901752
T3 - Communications in Computer and Information Science
SP - 424
EP - 432
BT - HCI International 2021 - Late Breaking Posters - 23rd HCI International Conference, HCII 2021, Proceedings
A2 - Stephanidis, Constantine
A2 - Antona, Margherita
A2 - Ntoa, Stavroula
PB - Springer Science and Business Media Deutschland GmbH
T2 - 23rd International Conference on Human-Computer Interaction, HCII 2021
Y2 - 24 July 2021 through 29 July 2021
ER -