Title :
Pixel-wise motion detection in persistent aerial video surveillance
Author_Institution :
Lawrence Livermore Nat. Lab., Livermore, CA, USA
Abstract :
We present a pixel-wise metric for change detection in stabilized, persistent aerial video. The method first decomposes a raw windowed temporal signal and performs time-frequency analysis to calculate a scalar value for each pixel. From this value, the algorithm indicates whether the pixel underwent independent motion in the time window or parallax. The method outlined does not make any assumptions on the sparsity of structural motion, amount of independent movement, nor calculate any camera geometry. The algorithm is naturally parallelizable and can be applied prior to Structure From Motion (SFM) frameworks to disambiguate independent and structural motion or create a mask for object-oriented video compression.
Keywords :
data compression; image motion analysis; object detection; time-frequency analysis; video coding; video surveillance; SFM; aerial video surveillance; change detection; object-oriented video compression; pixel scalar value calculation; pixel-wise motion detection; structure from motion frameworks; time-frequency analysis; windowed temporal signal decomposition; Cameras; Computer vision; Motion detection; Sensors; Signal resolution; Tracking;
Conference_Titel :
Computer Vision and Pattern Recognition Workshops (CVPRW), 2012 IEEE Computer Society Conference on
Conference_Location :
Providence, RI
Print_ISBN :
978-1-4673-1611-8
Electronic_ISBN :
2160-7508
DOI :
10.1109/CVPRW.2012.6239205