Title :
A real-time approach for autonomous detection and tracking of moving objects from UAV
Author :
Sadeghi-Tehran, Pouria ; Clarke, Christopher ; Angelov, Plamen
Author_Institution :
Intell. Syst. Lab., Lancaster Univ., Lancaster, UK
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.
Keywords :
autonomous aerial vehicles; image sensors; object detection; object tracking; robot vision; video signal processing; UAV; autonomous detection; moving camera; moving objects tracking; video analytics; Cameras; Clustering algorithms; Detectors; Feature extraction; Optical imaging; Robustness; Tracking; UAV; autonomous object detection; mobile visual surveillance platform;
Conference_Titel :
Evolving and Autonomous Learning Systems (EALS), 2014 IEEE Symposium on
Conference_Location :
Orlando, FL
DOI :
10.1109/EALS.2014.7009502