Robotics and Computer Vision Lab

Research Area

Project
2018.02.27 17:42

Megacity Modeling

JIT
조회 수 760 추천 수 0 댓글 0
?

단축키

Prev이전 문서

Next다음 문서

크게 작게 위로 아래로 댓글로 가기 인쇄 첨부
?

단축키

Prev이전 문서

Next다음 문서

크게 작게 위로 아래로 댓글로 가기 인쇄 첨부

_project_grn_pic0.PNG

 

 
 Members : Yunsu Bok, Yekeun Jeong, Jean-Charles Bazin, Donggeol Choi

 Associated center : National Research Foundation of Korea

 

Overview

The main objective of this research is “megacity modeling”. Reconstructing 3D structure is one of the fundamental issues of computer vision community. Several novel methods showed reasonable results, but the target of most researches was the object reconstruction in small-scale environment. Recently, the main issue of the 3D reconstruction has been changed into large-scale, such as huge buildings, ancient ruins, and cities.

This research is important in the historical point of view. Reconstructing the present appearance of a megacity is helpful for recording the change of the city on the time domain. Additionally, the 3D model of a megacity can be utilized in many applications. The manufacturers of car navigation system try to provide a realistic 3D model to help the drivers. This kind of system is not available yet, but the result of the megacity modeling will provide the precise information of the roads and structures nearby. The virtual sightseeing through the internet becomes more realistic using the result. This enhances the convenience and welfare of future society so that the busy or disabled people can travel the world.

 

 

fFVu7N3BYqYZe4w1VJRDaUWfU.png         PbvCfgu5WP6.png

 

 

In this research, we reconstruct 3D structure of the megacities using various sensors such as cameras, laser scanners and GPS. We collect information by capturing data on the ground and in the sky. We find the correspondences among the captured data and reconstruct 3D structure. Non-static objects such as pedestrians and cars must be removed.

The final result of this project is the 3D model of megacities such as Seoul or Daejeon, the sensor system to collect data, and the method of reconstruction using the data. We present the method of data collection using ground and aerial vehicles. We present the sensor system attached to the vehicles, and the details of data collection process, e.g. vehicle path, frame rate, etc. With enough sensor data, we develop the method of sampling data, localizing the system, and reconstructing static scenes with few human interactions. And we also present the method for efficient visualization such as data compression, texture mapping, etc.

The main application of the final result is the preservation of current scenes. The scenery in present days is a historically important material after several decades. We can recognize which part is changed as time passes at a glance. The result provides the information which typical photos cannot do, and is very useful for reconstructing the old scenes which is required for movies. Not only the past result, but also the present result can be used in various applications. We can pass through the reconstructed result and see any parts in any directions. Car navigation and virtual sightseeing would be good applications of the result.

 

 

1tZQJ3sENmUhYKHkmN.png

 

 

Publications

Capturing Village-level Heritages with a Hand-held Camera-Laser Fusion Sensor

  Yunsu Bok , Dong-Geol Choi , Yekeun Jeong , In So Kweon

  IEEE Workshop on eHeritage and Digital Art Preservation, In conjunction with ICCV 2009 , October 2009

 


  1. No Image

    Pixel-level Video Recognition and Understanding Projects

    Date2024.03.11 CategoryProject Views5
    Read More
  2. MTMMC: A Large-Scale Real-World Multi-Modal Camera Tracking Benchmark

    Date2024.03.11 CategoryProject Views46
    Read More
  3. [2021 Research Area] 1. Recognition

    Date2021.05.28 CategoryReasearch Area Views1559
    Read More
  4. [2021 Research Area] 2. Video and Language

    Date2021.05.28 CategoryReasearch Area Views432
    Read More
  5. [2021 Research Area] 3. Video Processing

    Date2021.05.28 CategoryReasearch Area Views428
    Read More
  6. [2021 Research Area] 4. Domain Adaptation

    Date2021.05.28 CategoryReasearch Area Views409
    Read More
  7. [2021 Research Area] 5. 3D and Depth Completion

    Date2021.05.28 CategoryReasearch Area Views1237
    Read More
  8. [2021 Research Area] 6. Adversarial Attack

    Date2021.05.28 CategoryReasearch Area Views29719
    Read More
  9. [2021 Research Area] 7. Multi-Modal Learning

    Date2021.05.28 CategoryReasearch Area Views1359
    Read More
  10. [2021 Research Area] 8. Machine Learning

    Date2021.05.28 CategoryReasearch Area Views288
    Read More
  11. [2021 Research Area] 9. Semi Supervised Learning

    Date2021.05.28 CategoryReasearch Area Views224
    Read More
  12. [2021 Research Area] 10. Sign Language

    Date2021.05.28 CategoryReasearch Area Views215
    Read More
  13. [2021 Research Area] 11. Vehicle and Robot

    Date2021.05.28 CategoryReasearch Area Views730
    Read More
  14. Visual Perception for Autonomous Driving in Day and Night

    Date2018.02.27 CategoryProject Views1090
    Read More
  15. Megacity Modeling

    Date2018.02.27 CategoryProject Views760
    Read More
  16. Intelligent Robot Vision System Research Center (Localization technology development Team)

    Date2018.02.27 CategoryProject Views562
    Read More
  17. i3D: Interactive Full 3D Service (Foreground/Background Segmentation Part)

    Date2018.02.27 CategoryProject Views517
    Read More
  18. National Research Lab: Development of Robust Vision Technology for Object Recognition and Shape Modeling of Intelligent Robot

    Date2018.02.27 CategoryProject Views606
    Read More
  19. Intelligent Robot Vision System Research Center (Detection Tracking Research Team)

    Date2018.02.27 CategoryProject Views723
    Read More
  20. [2018] RCV lab Research Fields

    Date2018.02.27 CategoryReasearch Area Views3905
    Read More
Board Pagination Prev 1 2 Next
/ 2