DocumentCode :
683717
Title :
Low Complexity Video Encoding and High Complexity Decoding for UAV Reconnaissance and Surveillance
Author :
Bhaskaranand, Malavika ; Gibson, Jerry D.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of California, Santa Barbara, Santa Barbara, CA, USA
fYear :
2013
fDate :
9-11 Dec. 2013
Firstpage :
163
Lastpage :
170
Abstract :
Conventional video compression schemes such as H.264/AVC use a high complexity encoder with block motion estimation (ME) and a low complexity, low latency decoder. However, unmanned aerial vehicle (UAV) reconnaissance and surveillance applications require low complexity encoders but can accommodate high complexity decoders. Moreover, the video sequences in these applications often primarily have global motion due to the known movement of the UAV and camera mounts. Motivated by this scenario, we propose and investigate a low complexity encoder with global motion based frame prediction and no block ME. For fly-over videos, our encoder achieves more than a 40% bit rate savings over a H.264 encoder with ME block size restricted to 8 × 8 and at lower complexity. We also develop a high complexity decoder based on Kalman filtering along motion trajectories and show average PSNR improvements of up to 0.5 dB with respect to a classic low complexity decoder.
Keywords :
Kalman filters; autonomous aerial vehicles; computational complexity; data compression; decoding; image sequences; motion estimation; video coding; video surveillance; H.264 encoder; H.264-AVC; Kalman filtering; ME block size; UAV movement; UAV reconnaissance-surveillance application; block ME; block motion estimation; camera mount; fly-over videos; global motion-based frame prediction; high-complexity decoders; high-complexity decoding; high-complexity encoder; low-complexity low-latency decoder; low-complexity video encoding; motion trajectory; unmanned aerial vehicle reconnaissance; video compression scheme; video sequences; Complexity theory; Decoding; Equations; Kalman filters; Mathematical model; Memory management; Transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia (ISM), 2013 IEEE International Symposium on
Conference_Location :
Anaheim, CA
Print_ISBN :
978-0-7695-5140-1
Type :
conf
DOI :
10.1109/ISM.2013.34
Filename :
6746786
Link To Document :
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