Sadeghi Tehran, Pouria and Clarke, Christopher and Angelov, Plamen Parvanov (2014) A real-time approach for autonomous detection and tracking of moving objects from UAV. In: 2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS) :. IEEE, GBR, pp. 43-49. ISBN 9781479944958
Full text not available from this repository.Abstract
A new approach to autonomously detect and track moving objects in a video captured by a moving camera from a UAV in real-time is proposed in this paper. The introduced approach replaces the need for a human operator to perform video analytics by autonomously detecting moving objects and clustering them for tracking purposes. The effectiveness of the introduced approach is tested on the footage taken from a real UAV and the evaluation results are demonstrated in this paper.