TY - GEN
T1 - Saliency-guided smoothing for 3D point clouds
AU - Yan, Feng
AU - Wang, Fei
AU - Guo, Yu
AU - Jiang, Peilin
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - To efficiently process 3D unorganized point clouds with noise and significant outliers, it is important to smooth the point clouds, but still retain faithfully the original surface geometry as much as possible. In this paper, we present a simple and fast saliency-guided smoothing method of 3D point. The method consists of three stages: firstly, saliency value for each point in noisy point clouds is calculated by site entropy rate method; secondly, robust vertex normal vector is updated by neighboring noisy normal vectors with weight terms related to detected visual saliency metrics; finally, based on least-squares error criterion, vertex position is updated with the integration of vertex normal vector. Analysis and experiments show the advantages of our proposed method over similar methods in the literature on synthetic data.
AB - To efficiently process 3D unorganized point clouds with noise and significant outliers, it is important to smooth the point clouds, but still retain faithfully the original surface geometry as much as possible. In this paper, we present a simple and fast saliency-guided smoothing method of 3D point. The method consists of three stages: firstly, saliency value for each point in noisy point clouds is calculated by site entropy rate method; secondly, robust vertex normal vector is updated by neighboring noisy normal vectors with weight terms related to detected visual saliency metrics; finally, based on least-squares error criterion, vertex position is updated with the integration of vertex normal vector. Analysis and experiments show the advantages of our proposed method over similar methods in the literature on synthetic data.
KW - 3D unorganized point clouds
KW - Saliency-guided smoothing
KW - Vertex normal vector updating
KW - Vertex position updating
UR - https://www.scopus.com/pages/publications/85027711093
U2 - 10.1007/978-3-319-63309-1_16
DO - 10.1007/978-3-319-63309-1_16
M3 - 会议稿件
AN - SCOPUS:85027711093
SN - 9783319633084
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 165
EP - 174
BT - Intelligent Computing Theories and Application - 13th International Conference, ICIC 2017, Proceedings
A2 - Huang, De-Shuang
A2 - Premaratne, Prashan
A2 - Bevilacqua, Vitoantonio
A2 - Gupta, Phalguni
PB - Springer Verlag
T2 - 13th International Conference on Intelligent Computing, ICIC 2017
Y2 - 7 August 2017 through 10 August 2017
ER -