Please help transcribe this video using our simple transcription tool. You need to be logged in to do so.


We describe an imaging architecture for compressive video sensing termed programmable pixel compressive camera (P2C2). P2C2 allows us to capture fast phenom- ena 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 reconstruc- tion 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 redundan- cies in a video volume, one can faithfully recover the un- derlying high-speed video frames from the observed low speed coded video. The imaging architecture and the re- construction 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.

Questions and Answers

You need to be logged in to be able to post here.