University of Arizona
Browse
TEXT
README.txt (3.11 kB)
VIDEO
Visualization 2.mp4 (2.02 MB)
DOCUMENT
Exp_fig_1.pdf (553.39 kB)
DOCUMENT
Exp_fig_7.pdf (215.87 kB)
ARCHIVE
data.zip (79.61 MB)
1/0
5 files

Test dataset for Compressive video via IR-pulsed illumination

dataset
posted on 2023-11-02, 17:56 authored by James Tyler SkowronekJames Tyler Skowronek, Felipe Guzman, Esteban Vera, David J. Brady

Compressive video via IR-pulsed illumination. Refer to publication for details.

We propose and demonstrate a compressive temporal imaging system based on pulsed illumination to encode temporal dynamics into the imaging sensor during exposure time. Our approach enables >10x increase in effective frame rate without increasing camera complexity. To mitigate the complexity of the inverse problem during reconstruction, we introduce two keyframes: one before and one after the coded frame. We also craft a novel deep learning architecture for improved reconstruction of the high-speed scenes. Simulation and experimental results clearly demonstrate the reconstruction of high-quality, high-speed videos from the compressed data.



For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to data-management@arizona.edu

History

Usage metrics

    Science & Mathematics

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC