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  1. Journal of Imaging
  2. Volume: 3
  3. Issue: 2
  4. 3D Reconstructions Using Unstabilized Video Footage from an Unmanned Aerial Vehicle
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Volume: 4
Volume: 3
Issue: 4
Issue: 3
Issue: 2
Measuring Leaf Thickness with 3D Close-Up Laser Scanners: Possible or Not?
Object Recognition in Aerial Images Using Convolutional Neural Networks
Memory Efficient VLSI Implementation of Real-Time Motion Detection System Using FPGA Platform
A Multi-Projector Calibration Method for Virtual Reality Simulators with Analytically Defined Screens
Real-Time FPGA-Based Object Tracker with Automatic Pan-Tilt Features for Smart Video Surveillance Systems
Depth Estimation for Lytro Images by Adaptive Window Matching on EPI
Tangent-Based Binary Image Abstraction
3D Reconstructions Using Unstabilized Video Footage from an Unmanned Aerial Vehicle
A Novel Vision-Based Classification System for Explosion Phenomena
An Overview of Infrared Remote Sensing of Volcanic Activity
Issue: 1
Volume: 2
Volume: 1

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Reconstructions Using UnstabilizedVideo Footage from an Unmanned Aerial Vehicle

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3D Reconstructions Using Unstabilized Video Footage from an Unmanned Aerial Vehicle

Content Provider MDPI
Author Byrne, Jonathan O'Keeffe, Evan Lennon, Donal Laefer, Debra F.
Abstract Structure from motion (SFM) is a methodology for automatically reconstructing three-dimensional (3D) models from a series of two-dimensional (2D) images when there is no a priori knowledge of the camera location and direction. Modern unmanned aerial vehicles (UAV) now provide a low-cost means of obtaining aerial video footage of a point of interest. Unfortunately, raw video lacks the required information for SFM software, as it does not record exchangeable image file (EXIF) information for the frames. In this work, a solution is presented to modify aerial video so that it can be used for photogrammetry. The paper then examines how the field of view effects the quality of the reconstruction. The input is unstabilized, and distorted video footage obtained from a low-cost UAV which is then combined with an open-source SFM system to reconstruct a 3D model. This approach creates a high quality reconstruction by reducing the amount of unknown variables, such as focal length and sensor size, while increasing the data density. The experiments conducted examine the optical field of view settings to provide sufficient overlap without sacrificing image quality or exacerbating distortion. The system costs less than e1000, and the results show the ability to reproduce 3D models that are of centimeter-level accuracy. For verification, the results were compared against millimeter-level accurate models derived from laser scanning.
File Size 6426624
File Format PDF
e-ISSN 2313433X
DOI 10.3390/jimaging3020015
Journal Journal of Imaging
Issue Number 2
Volume Number 3
Language English
Publisher Date 2017-04-22
Access Restriction Open
Subject Keyword structure from motion unmanned aerial vehicles 3D model aerial video
Content Type Text
Resource Type Article
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