TY - GEN
T1 - Real-time 3D scene modeling using dynamic billboard for remote robot control systems
AU - Chu, Phuong Minh
AU - Cho, Seoungjae
AU - Nguyen, Hieu Trong
AU - Sim, Sungdae
AU - Kwak, Kiho
AU - Cho, Kyungeun
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/7
Y1 - 2017/12/7
N2 - In this paper, a method for modeling three-dimensional scenes from a Lidar point cloud as well as a billboard calibration approach for remote mobile robot control applications are presented as a combined two-step approach. First, by projecting a local three-dimensional point cloud on two-dimensional coordinate system, we obtain a list of colored points. Based on this list, we apply a proposed ground segmentation algorithm to separate ground and non-ground areas. With the ground part, a dynamic triangular mesh is created by means of a height map and the vehicle position. The non-ground part is divided into small groups. Then, a local voxel map is applied for modeling each group. As a result, all the inner surfaces are eliminated. Second, for billboard calibration, we implement three stages in each frame. In the first stage, at the billboard location, an average ground point is estimated. In the second stage, the distortion angle is calculated. The billboard is updated for each frame in the final stage and corresponds to the terrain gradient.
AB - In this paper, a method for modeling three-dimensional scenes from a Lidar point cloud as well as a billboard calibration approach for remote mobile robot control applications are presented as a combined two-step approach. First, by projecting a local three-dimensional point cloud on two-dimensional coordinate system, we obtain a list of colored points. Based on this list, we apply a proposed ground segmentation algorithm to separate ground and non-ground areas. With the ground part, a dynamic triangular mesh is created by means of a height map and the vehicle position. The non-ground part is divided into small groups. Then, a local voxel map is applied for modeling each group. As a result, all the inner surfaces are eliminated. Second, for billboard calibration, we implement three stages in each frame. In the first stage, at the billboard location, an average ground point is estimated. In the second stage, the distortion angle is calculated. The billboard is updated for each frame in the final stage and corresponds to the terrain gradient.
UR - http://www.scopus.com/inward/record.url?scp=85042368554&partnerID=8YFLogxK
U2 - 10.1109/MFI.2017.8170454
DO - 10.1109/MFI.2017.8170454
M3 - Conference contribution
AN - SCOPUS:85042368554
T3 - IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
SP - 354
EP - 358
BT - MFI 2017 - 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2017
Y2 - 16 November 2017 through 18 November 2017
ER -