NDLI: P2C2: Programmable pixel compressive camera for high speed imaging

Content Provider	IEEE Xplore Digital Library
Author	Reddy, D. Veeraraghavan, A. Chellappa, R.
Copyright Year	2011
Description	Author affiliation: University of Maryland, College Park, MD, 20742 (Reddy, D.; Chellappa, R.) \|\| Mitsubishi Electric Research Labs, Cambridge, MA, 02139 (Veeraraghavan, A.)
Abstract	We describe an imaging architecture for compressive video sensing termed programmable pixel compressive camera (P2C2). P2C2 allows us to capture fast phenomena at frame rates higher than the camera sensor. In P2C2, each pixel has an independent shutter that is modulated at a rate higher than the camera frame-rate. The observed intensity at a pixel is an integration of the incoming light modulated by its specific shutter. We propose a reconstruction algorithm that uses the data from P2C2 along with additional priors about videos to perform temporal super-resolution. We model the spatial redundancy of videos using sparse representations and the temporal redundancy using brightness constancy constraints inferred via optical flow. We show that by modeling such spatio-temporal redundancies in a video volume, one can faithfully recover the underlying high-speed video frames from the observed low speed coded video. The imaging architecture and the reconstruction algorithm allows us to achieve temporal super-resolution without loss in spatial resolution. We implement a prototype of P2C2 using an LCOS modulator and recover several videos at 200 fps using a 25 fps camera.
Starting Page	329
Ending Page	336
File Size	5533378
Page Count	8
File Format	PDF
ISBN	9781457703942
ISSN	10636919
e-ISBN	9781457703959
DOI	10.1109/CVPR.2011.5995542
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cameras Spatial resolution Liquid crystal on silicon Brightness Modulation
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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