Loading...

Prediction of aerial-image motion blurs due to the flying vehicle dynamics and camera characteristics in a virtual environment

Atashgah, M. A ; Sharif University of Technology | 2013

922 Viewed
  1. Type of Document: Article
  2. DOI: 10.1177/0954410012450107
  3. Publisher: 2013
  4. Abstract:
  5. This study presents comprehensive studies on practical means to predict aerial-image motion blurs due to the flying vehicle dynamics, including flying altitude; cruising speed; and angular velocities and finally installed camera characteristics; such as, frame rate and image size. The resulting predictions of blur values are in-turn used to generate blurry images to be fed as input data for later use in a de-blurring-in-the-loop of a Mono-simultaneous localization and mapping system. The whole process is coordinated by means of an integrated aerial virtual environment. The integrated aerial virtual environment consists of a three-dimensional graphical engine which could communicate with a full six-degrees of freedom aircraft dynamic simulator to precisely generate trajectories of the flying vehicle. Any accumulated real-time image taken by the camera installed on the aircraft during its mission considers the relevant vehicle states for necessary adjustments. We practically exploit C++, High-Level Shader Language, as well as JSBSim to expand the components of the package. Extensive case- studies show that the developed approach is quite effective in controlled environments
  6. Keywords:
  7. Aerial image ; Flight simulation ; Motion blur camera state ; Three-dimensional graphics engine ; Aerial images ; Aircraft dynamics ; Controlled environment ; Localization and mappings ; Motion blur ; Real-time images ; Three-dimensional graphics ; Cameras ; Engines ; Flight simulators ; High level languages ; Mathematical techniques ; Virtual reality ; Vehicles
  8. Source: Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering ; Volume 227, Issue 7 , 2013 , Pages 1055-1067 ; 09544100 (ISSN)
  9. URL: http://pig.sagepub.com/content/227/7/1055