@inproceedings{Leonidas2015b,
abstract = {The maximum achievable frame-rate for a video camera is limited by the sensor's pixel readout rate. The same sensor may achieve either a slow frame-rate at full resolution (e.g., 60 fps at 4 Mpixel resolution) or a fast frame-rate at low resolution (e.g., 240 fps at 1 Mpixel resolution). Higher frame-rates are achieved using pixel readout modes (e.g., subsampling or binning) that sacrifice spatial for temporal resolution within a fixed bandwidth. A number of compressive video cameras have been introduced to overcome this fixed bandwidth constraint and achieve high frame-rates without sacrificing spatial resolution. These methods use electro-optic components (e.g., LCoS, DLPs, piezo actuators) to introduce high speed spatio-temporal multiplexing in captured images. Full resolution, high speed video is then restored by solving an undetermined system of equations using a sparse regularization framework. In this work, we introduce the first all-digital temporal compressive video camera that uses custom subsampling modes to achieve spatio-temporal multiplexing. Unlike previous compressive video cameras, ours requires no additional optical components, enabling it to be implemented in a compact package such as a mobile camera module. We demonstrate results using a TrueSense development kit with a 12 Mpixel sensor and programmable FPGA read out circuitry.},
author = {Spinoulas, Leonidas and He, Kuan and Cossairt, Oliver and Katsaggelos, Aggelos},
booktitle = {2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
doi = {10.1109/CVPRW.2015.7301375},
isbn = {978-1-4673-6759-2},
issn = {21607516},
keywords = {Cameras,Compressed sensing,Image reconstruction,Registers,Spatial resolution,Video sequences},
month = {jun},
pages = {49--57},
publisher = {IEEE},
title = {{Video compressive sensing with on-chip programmable subsampling}},
url = {http://ieeexplore.ieee.org/document/7301375/},
volume = {2015-Octob},
year = {2015}
}

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These methods use electro-optic components (e.g., LCoS, DLPs, piezo actuators) to introduce high speed spatio-temporal multiplexing in captured images. Full resolution, high speed video is then restored by solving an undetermined system of equations using a sparse regularization framework. In this work, we introduce the first all-digital temporal compressive video camera that uses custom subsampling modes to achieve spatio-temporal multiplexing. Unlike previous compressive video cameras, ours requires no additional optical components, enabling it to be implemented in a compact package such as a mobile camera module. 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