Optical compressive change and motion detection

Yuval Kashter, Ofer Levi, Adrian Stern

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)2491-2496
Number of pages6
JournalApplied Optics
Issue number13
StatePublished - 1 May 2012
Externally publishedYes


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