Topology driven 3D mesh hierarchical segmentation

被引:36
|
作者
Tierny, Julien [1 ]
Vandeborre, Jean-Philippe [1 ,2 ]
Daoudi, Mohamed [1 ,2 ]
机构
[1] Univ Lille, LIFL, CNRS, UMR USTL 8022, Lille, France
[2] GET INT TELECOM Lille 1, Lille, France
关键词
D O I
10.1109/SMI.2007.38
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In this paper we propose to address the semantic-oriented 3D mesh hierarchical segmentation problem, using enhanced topological skeletons [18]. This high level information drives both the feature boundary computation as well as the feature hierarchy definition. Proposed hierarchical scheme is based on the key idea that the topology of a feature is a more important decomposition criterion than its geometry. First, the enhanced topological skeleton of the input triangulated surface is constructed. Then it is used to delimit the core of the object and to identify junction areas. This second step results in a fine segmentation of the object. Finally, a fine to coarse strategy enables a semantic-oriented hierarchical composition of features, subdividing human limbs into arms and hands for example. Method performance is evaluated according to seven criteria enumerated in latest segmentation surveys [3]. Thanks to the high level description it uses as an input, presented approach results, with low computation times, in robust and meaningful compatible hierarchical decompositions.
引用
收藏
页码:215 / +
页数:3
相关论文
共 50 条
  • [1] Laplacian Mesh Transformer: Dual Attention and Topology Aware Network for 3D Mesh Classification and Segmentation
    Li, Xiao-Juan
    Yang, Jie
    Zhang, Fang-Lue
    [J]. COMPUTER VISION, ECCV 2022, PT XXIX, 2022, 13689 : 541 - 560
  • [2] A Benchmark for 3D Mesh Segmentation
    Chen, Xiaobai
    Golovinskiy, Aleksey
    Funkhouser, Thomas
    [J]. ACM TRANSACTIONS ON GRAPHICS, 2009, 28 (03):
  • [3] Protrusion Guided 3D Mesh Segmentation
    Chen, Hung-Kuang
    Chen, Yung-Cheng
    [J]. PROCEEDINGS OF 3RD INTERNATIONAL CONFERENCE ON MULTIMEDIA TECHNOLOGY (ICMT-13), 2013, 84 : 1396 - 1403
  • [4] Volumetric Segmentation of 3D Mesh Models
    Sun, Guangsheng
    Yan, Jingqi
    [J]. INTERNATIONAL ACADEMIC CONFERENCE ON THE INFORMATION SCIENCE AND COMMUNICATION ENGINEERING (ISCE 2014), 2014, : 114 - 120
  • [5] Learning 3D Mesh Segmentation and Labeling
    Kalogerakis, Evangelos
    Hertzmann, Aaron
    Singh, Karan
    [J]. ACM TRANSACTIONS ON GRAPHICS, 2010, 29 (04):
  • [6] Towards a Parameterless 3D Mesh Segmentation
    Farag, Sara
    Abdelrahman, Wael
    Nahavandi, Saeid
    Creighton, Douglas
    [J]. INTERNATIONAL CONFERENCE ON GRAPHIC AND IMAGE PROCESSING (ICGIP 2012), 2013, 8768
  • [7] Hierarchical Aggregation for 3D Instance Segmentation
    Chen, Shaoyu
    Fang, Jiemin
    Zhang, Qian
    Liu, Wenyu
    Wang, Xinggang
    [J]. 2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021), 2021, : 15447 - 15456
  • [8] Unbiased watershed hierarchical 3D segmentation
    Betser, J
    Delest, S
    Boné, R
    [J]. PROCEEDINGS OF THE FIFTH IASTED INTERNATIONAL CONFERENCE ON VISUALIZATION, IMAGING, AND IMAGE PROCESSING, 2005, : 412 - 417
  • [9] Statistical mesh distributions for 3D object topology
    Qasaimeh, Malik
    Zhang, Ying
    Thrinissi, Khaled
    Ben Hamza, A.
    [J]. 2007 9TH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS, VOLS 1-3, 2007, : 61 - 64
  • [10] 3D TOOTH MESH SEGMENTATION WITH SIMPLIFIED MESH CELL REPRESENTATION
    Jana, Ananya
    Subhash, Hrebesh Molly
    Metaxas, Dimitris
    [J]. 2023 IEEE 20TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING, ISBI, 2023,