Research on a three-dimensional reconstruction method based on the feature matching algorithm of a scale-invariant feature transform

被引：9
|
作者：
Hu, Yingfeng [1 ]
机构：
[1] E China Jiaotong Univ, Sch Railway Tracks & Transportat, Nanchang 330013, Peoples R China
来源：
MATHEMATICAL AND COMPUTER MODELLING | 2011年 / 54卷 / 3-4期
关键词：
Feature matching; 3D reconstruction; Scale-invariant feature transform; Non-coplanar lines; Binocular stereo vision;
D O I：
10.1016/j.mcm.2010.11.016
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Currently, reverse engineering has attracted increasing attention in the non-destructive detection field, since it is a viable method to create a three-dimensional (3D) virtual model of an existing physical part. Feature points matching and 3D reconstruction are critical processes in reverse engineering of binocular stereo vision. In this paper, we present a 3D reconstruction method based on the feature matching algorithm of a scale-invariant feature transform (SIFT). First, we find the paired matching pixel points in the two corresponding digital images by using the SIFT matching algorithm. Second, the middle points on the common perpendicular of non-coplanar lines are exploited to estimate the 3D points. Finally, experimental results are presented to demonstrate the practicality of the proposed method. Published by Elsevier Ltd
引用
收藏
页码：919 / 923
页数：5
相关论文
共 50 条
  • [41] Multiple vehicles detection and tracking based on scale-invariant feature transform
    Choi, Jae-Young
    Sung, Kyung-Sang
    Yang, Young-Kyu
    2007 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE, VOLS 1 AND 2, 2007, : 349 - 354
  • [42] FPGA-based hardware design for scale-invariant feature transform
    Li S.-A.
    Wang W.-Y.
    Pan W.-Z.
    Hsu C.-C.J.
    Lu C.-K.
    Hsu, Chen-Chien James (jhsu@ntnu.edu.tw), 2018, Institute of Electrical and Electronics Engineers Inc., United States (06) : 43850 - 43864
  • [43] Relaxation Based Matching of Clusters of Keypoints from Scale-Invariant Feature Transform on Multiple Frames of Buildings
    Lee, Sunmin
    Kim, Yong Cheol
    2015 IEEE 9TH INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING (WISP), 2015, : 56 - 60
  • [44] Scale Invariant Feature Transform Based Image Matching and Registration
    Kher, Heena R.
    Thakar, Vishvjit K.
    2014 FIFTH INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING (ICSIP 2014), 2014, : 50 - 55
  • [45] Research and Implementation of Binocular Distance Measurement System Based on Improved Scale-Invariant Feature Transform Algorithm with Parallel Acceleration
    Zhang Zhiqiang
    Shi Wenhua
    LASER & OPTOELECTRONICS PROGRESS, 2019, 56 (14)
  • [46] Lung feature tracking in 4D-MRI using a scale-invariant feature transform method
    Colvill, Emma
    STRAHLENTHERAPIE UND ONKOLOGIE, 2019, 195 (06) : 601 - 601
  • [47] Lung Feature Tracking in 4D-MRI Using a Scale-Invariant Feature Transform Method
    Colvill, E. ColvillE
    Lomax, A.
    Bieri, O.
    Celicanin, Z.
    Weber, D.
    Peroni, M.
    MEDICAL PHYSICS, 2018, 45 (06) : E193 - E193
  • [48] Three-dimensional Object Recognition via Integral Imaging and Scale Invariant Feature Transform
    Yi, Faliu
    Moon, Inkyu
    THREE-DIMENSIONAL IMAGING, VISUALIZATION, AND DISPLAY 2014, 2014, 9117
  • [49] FPGA Design of Enhanced Scale-Invariant Feature Transform with Finite-Area Parallel Feature Matching for Stereo Vision
    Kuo, Chien-Hung
    Huang, Erh-Hsu
    Chien, Chiang-Heng
    Hsu, Chen-Chien
    ELECTRONICS, 2021, 10 (14)
  • [50] Classification of Histopathological Images using Scale-Invariant Feature Transform
    Bukala, Andrzej
    Cyganek, Boguslaw
    Koziarski, Michal
    Kwolek, Bogdan
    Olborski, Boguslaw
    Antosz, Zbigniew
    Swadzba, Jakub
    Sitkowski, Piotr
    PROCEEDINGS OF THE 15TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS, VOL 5: VISAPP, 2020, : 506 - 512
12345