DocumentCode :
595173
Title :
Efficient UAV video event summarization
Author :
Hoang Trinh ; Jun Li ; Miyazawa, Shintaro ; Moreno, J. ; Pankanti, Sharath
fYear :
2012
fDate :
11-15 Nov. 2012
Firstpage :
2226
Lastpage :
2229
Abstract :
In the paper, we present an approach to efficiently summarizing UAV video data. Our approach is based on first detecting and tracking moving objects. Significant camera motion usually present in UAV video data is successfully handled by a robust feature-based frame registration technique. We then devise a saliency-based scoring method to score and rank detected object tracks. Object tracks are then grouped into video segments. The final step is to generate a concise summarization and visualization. Experimental results on the VIRAT UAV dataset show that we can accomplish a data reduction rate in excess of 1000 without significantly missing any activities of interest.
Keywords :
autonomous aerial vehicles; data reduction; data visualisation; image motion analysis; image registration; object detection; object tracking; video signal processing; UAV video data; UAV video event summarization; VIRAT UAV dataset; camera motion; data reduction rate; detected object track ranking; detected object track scoring; moving object detection; moving object tracking; robust feature-based frame registration technique; saliency-based scoring method; unmanned aerial vehicle; video segments; Cameras; Image segmentation; Mathematical model; Robustness; Surveillance; Target tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
ISSN :
1051-4651
Print_ISBN :
978-1-4673-2216-4
Type :
conf
Filename :
6460606
Link To Document :
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