Title :
Compressive sensing in video applications
Author :
Orovic, Irena ; Park, Soojin ; Stankovic, Stevan
Author_Institution :
Fac. of Electr. Eng., Univ. of Montenegro, Podgorica, Montenegro
Abstract :
In this paper, a new approach to estimate motion parameters in compressive sensed video sequences is proposed. The proposed procedure combines sparse reconstruction algorithms and time-frequency analysis applied to μ-propagation signal. This concept allows providing precise velocity estimation even under a reduced number of randomly chosen video frames. The theory is applied and illustrated on synthetic and real video sequence.
Keywords :
compressed sensing; image reconstruction; image sequences; motion estimation; time-frequency analysis; video signal processing; μ-propagation signal; compressive sensed video sequences; motion parameter estimation; sparse reconstruction algorithms; time-frequency analysis; velocity estimation; video frames; Compressed sensing; Estimation; Frequency estimation; Time-frequency analysis; Vectors; Video sequences; Compressive sensing; motion parameters estimation; random frames recording; reconstruction algorithms; velocity; video signals;
Conference_Titel :
Telecommunications Forum (TELFOR), 2013 21st
Conference_Location :
Belgrade
Print_ISBN :
978-1-4799-1419-7
DOI :
10.1109/TELFOR.2013.6716337
