Graph cut based multiple view segmentation for 3D reconstruction

被引:0
|
作者
Sormann, Mario [1 ]
Zach, Christopher [1 ]
Kamer, Konrad [1 ]
机构
[1] VRVis Res Ctr, Inffeldgasse 16-2, A-8010 Graz, Austria
关键词
D O I
暂无
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 a novel framework for efficiently extracting foreground objects in so called short-baseline image sequences. We apply the obtained segmentation to improve subsequent 3D reconstruction results. Essentially, our framework combines a graph cut based optimization algorithm with an intuitive user interface. At first a meanshift segmentation algorithm partitions each image of the sequence into a certain number of regions. Additionally we provide an intelligent graphical user interface for easy specification of foreground as well as background regions across all images of the sequence. Within the graph cut optimization algorithm we define new energy terms to increase the robustness and to keep the segmentation of the foreground object coherent across all images of the sequence. Finally, a refined graph cut segmentation and several adjustment operations allow an accurate and effective foreground extraction. The obtained results are demonstrated on several real world data sets.
引用
收藏
页码:1085 / 1092
页数:8
相关论文
共 50 条
  • [1] Graph-cut-based 3D Model Segmentation for Articulated Object Reconstruction
    Han, Inkyu
    Kim, Hyoungnyoun
    Park, Ji-Hyung
    2011 10TH IEEE INTERNATIONAL SYMPOSIUM ON MIXED AND AUGMENTED REALITY (ISMAR), 2011,
  • [2] A Method of 3D Reconstruction from Multiple Views Based on Graph Theoretic Segmentation
    Li, Yi
    Hong, Hanyu
    Zhang, Xiuhua
    Bai, Haoyu
    MIPPR 2013: PATTERN RECOGNITION AND COMPUTER VISION, 2013, 8919
  • [3] Learning Superpoint Graph Cut for 3D Instance Segmentation
    Hui, Le
    Tang, Linghua
    Shen, Yaqi
    Xie, Jin
    Yang, Jian
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 35 (NEURIPS 2022), 2022,
  • [4] 3D automatic anatomy segmentation based on iterative graph-cut-ASM
    Chen, Xinjian
    Bagci, Ulas
    MEDICAL PHYSICS, 2011, 38 (08) : 4610 - 4622
  • [5] 3D Model Reconstruction Based on Multiple View Image Capture
    Lee, Po-Han
    Huang, Jui-Wen
    Lin, Huei-Yung
    IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING AND COMMUNICATIONS SYSTEMS (ISPACS 2012), 2012,
  • [6] SAM-Guided Graph Cut for 3D Instance Segmentation
    Guo, Haoyu
    Zhu, He
    Peng, Sida
    Wang, Yuang
    Shen, Yujun
    Hu, Ruizhen
    Zhou, Xiaowei
    COMPUTER VISION - ECCV 2024, PT XLVIII, 2025, 15106 : 234 - 251
  • [7] Multiscale Graph-Cut for 3D Segmentation of Compact Objects
    Jirik, Miroslav
    Lukes, Vladimir
    Zelezny, Milos
    Liska, Vaclav
    COMBINATORIAL IMAGE ANALYSIS, IWCIA 2018, 2018, 11255 : 227 - 236
  • [8] Differential and Relaxed Image Foresting Transform for Graph-Cut Segmentation of Multiple 3D Objects
    Moya, Nikolas
    Falcao, Alexandre X.
    Ciesielski, Krzysztof C.
    Udupa, Jayaram K.
    MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2014, PT I, 2014, 8673 : 690 - +
  • [10] On Multiple-view Matrix Based 3D Reconstruction from Multiple-view Images
    Huang, Huimin
    Zhao, Ruibin
    Pang, Mingyong
    2018 INTERNATIONAL CONFERENCE ON CYBERWORLDS (CW), 2018, : 114 - 119