Localization information of moving and changing objects, as commonly extracted from video sequences, is typically very sparse with respect to the full data frames, thus fulfilling one of the basic conditions of compressive sensing theory. Motivated by this observation, we developed an optical compressive change and motion-sensing technique that detects the location of moving objects by using a significantly fewer samples than conventionally taken. We present examples of motion detection and motion tracking with over two orders of magnitude fewer samples than required with conventional systems.
© 2012 Optical Society of America
Original Manuscript: January 23, 2012
Revised Manuscript: March 12, 2012
Manuscript Accepted: March 23, 2012
Published: May 1, 2012
Yuval Kashter, Ofer Levi, and Adrian Stern, "Optical compressive change and motion detection," Appl. Opt. 51, 2491-2496 (2012)