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Omni Directional Moving Object Detection and Tracking With Virtual Reality Feedback

[+] Author Affiliations
Armaan Zirakchi, Cody Lee Lundberg, Hakki Erhan Sevil

University of Texas at Arlington Research Institute (UTARI), Fort Worth, TX

Paper No. DSCC2017-5352, pp. V002T21A012; 6 pages
  • ASME 2017 Dynamic Systems and Control Conference
  • Volume 2: Mechatronics; Estimation and Identification; Uncertain Systems and Robustness; Path Planning and Motion Control; Tracking Control Systems; Multi-Agent and Networked Systems; Manufacturing; Intelligent Transportation and Vehicles; Sensors and Actuators; Diagnostics and Detection; Unmanned, Ground and Surface Robotics; Motion and Vibration Control Applications
  • Tysons, Virginia, USA, October 11–13, 2017
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5828-8
  • Copyright © 2017 by ASME


Computer vision methods are commonly used to detect and track motion using conventional cameras, however, that is limited with the field of view (FOV) of the camera. This study is to attempt to overcome this challenge by using a 360 degree camera. Our approach utilizes background subtracter from OpenCV Library which creates a continuously updating background model for the motion detection. The model is subtracted from the current frame leaving contours symbolizing the movement observed in the camera view. These contours are then analyzed and processed so that the system can track the largest contour. The tracked movement is outlined and directed to the user via Virtual Reality (VR) headset. The VR headset only displays a 60 degree portion of the camera view to the user which provides more realistic situational awareness of the surroundings for the user. These activities are a part of a larger effort to establish a foundation for autonomous unmanned vehicle systems with situational awareness capabilities.

Copyright © 2017 by ASME



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