Parallel line-based structure from motion by using omnidirectional camera in textureless scene

被引:11
|
作者
Kawanishi, Ryosuke [1 ]
Yamashita, Atsushi [1 ]
Kaneko, Toru [1 ]
Asama, Hajime [1 ]
机构
[1] Univ Tokyo, Dept Precis Engn, Bunkyo Ku, Tokyo 1138656, Japan
关键词
structure from motion; parallel lines; textureless scene; omnidirectional camera; RECONSTRUCTION;
D O I
10.1080/01691864.2013.751160
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
In this paper, we propose a reconstruction method for a 3D structure using sequential omnidirectional images in an artificial environment. The proposed method is fundamentally categorized into the Structure from Motion (SfM) technique. The conventional point-based SfM using a standard camera is, however, likely to fail to recover a 3D structure in an artificial and textureless environment such as a corridor. To tackle this problem, the proposed technique uses an omnidirectional camera and line-based SfM. Line features, such as a borderline of a wall and a floor or a window frame, are easy to discern in an artificial environment comparing point features, even in a textureless scene. In addition, an omnidirectional camera can track features for a long period because of its wide field-of-view. Extracted line features in an artificial environment are often mutually parallel. Parallel lines provide valuable constraints for camera movement estimation. Directions and locations of lines are estimated simultaneously with 3D camera movements. A 3D model of the environment is constructed from measurement results of lines and edge points. Experimental results show the effectiveness of our proposed method.
引用
收藏
页码:19 / 32
页数:14
相关论文
共 50 条
  • [21] Digital image correlation with a moving camera using structure from motion calibration
    Barros, Francisco
    Sousa, Pedro J.
    Tavares, Paulo J.
    Moreira, Pedro M. G. P.
    3RD INTERNATIONAL CONFERENCE ON STRUCTURAL INTEGRITY (ICSI 2019), 2019, 17 : 986 - 991
  • [22] A Simplified Solution to Motion Estimation Using an Omnidirectional Camera and a 2-D LRF Sensor
    Hoang, Van-Dung
    Jo, Kang-Hyun
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2016, 12 (03) : 1064 - 1073
  • [23] Graph-based parallel large scale structure from motion
    Chen, Yu
    Shen, Shuhan
    Chen, Yisong
    Wang, Guoping
    PATTERN RECOGNITION, 2020, 107
  • [24] Visual SLAM Based on EKF Filtering Algorithm from Omnidirectional Camera
    Chen Hui
    Ma Shiwei
    PROCEEDINGS OF 2013 IEEE 11TH INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS (ICEMI), 2013, : 660 - 663
  • [25] Fast incremental structure from motion based on parallel bundle adjustment
    Mingwei Cao
    Liping Zheng
    Wei Jia
    Xiaoping Liu
    Journal of Real-Time Image Processing, 2021, 18 : 379 - 392
  • [26] Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences
    Becker, Florian
    Lenzen, Frank
    Kappes, Joerg H.
    Schnoerr, Christoph
    INTERNATIONAL JOURNAL OF COMPUTER VISION, 2013, 105 (03) : 269 - 297
  • [27] MCSfM: Multi-Camera-Based Incremental Structure-From-Motion
    Cui, Hainan
    Gao, Xiang
    Shen, Shuhan
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2023, 32 : 6441 - 6456
  • [28] Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences
    Florian Becker
    Frank Lenzen
    Jörg H. Kappes
    Christoph Schnörr
    International Journal of Computer Vision, 2013, 105 : 269 - 297
  • [29] Fast incremental structure from motion based on parallel bundle adjustment
    Cao, Mingwei
    Zheng, Liping
    Jia, Wei
    Liu, Xiaoping
    JOURNAL OF REAL-TIME IMAGE PROCESSING, 2021, 18 (02) : 379 - 392
  • [30] DETECTION OF CRITICAL CAMERA CONFIGURATIONS FOR STRUCTURE FROM MOTION
    Michelini, Mario
    Mayer, Helmut
    EUROPEAN CALIBRATION AND ORIENTATION WORKSHOP (EUROCOW 2014), 2014, : 73 - 78