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Vision-Based Horizon Detection and Target Tracking for UAVs

  • Yingju Chen
  • Ahmad Abushakra
  • Jeongkyu Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6939)

Abstract

Unmanned Aerial Vehicle (UAV) has been deployed in a variety of applications like remote traffic surveillance, dangerous area observation, and mine removal, since it is able to overcome the limitations of ground vehicles. It can also be used for traffic controlling, border patrolling, accident and natural disaster monitoring for search and rescue purpose. There are two important tasks in the UAV system, automatic stabilization and target tracking. Automatic stabilization makes a UAV fully autonomous, while target tracking alleviates the overhead of a manual system. In order to address these, we present computer vision based horizon detection and target tracking for the videos captured by UAV camera. The proposed horizon detection algorithm is an enhancement of the Cornall’s Theorem and our target tracking employs optical flow. The results of both real and simulated videos show that the proposed algorithms are promising.

Keywords

Unman Aerial Vehicle Target Tracking Roll Angle Automatic Stabilization Unman Aerial Vehicle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Yingju Chen
    • 1
  • Ahmad Abushakra
    • 1
  • Jeongkyu Lee
    • 1
  1. 1.Department of Computer Science and EngineeringUniversity of BridgeportBridgeportUSA

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