| Paper Abstract and Keywords |
| Presentation |
2018-11-28 16:30
[Poster Presentation]
Joint optimization for compressive video sensing and reconstruction under hardware constraints
Michitaka Yoshida (Kyushu Univ.), Akihiko Torii, Masatoshi Okutomi (Tokyo Tech), Kenta Endo, Yukinobu Sugiyama (Hamamatsu Photonics K. K.), RIn-ichiro Taniguchi (Kyushu Univ.), Hajime Nagahara (Osaka Univ.) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Compressive video sensing is the process of encoding multiple sub-frames into a single frame with controlled sensor exposures and reconstructing the sub-frames from the single compressed frame. It is known that spatially and temporally random exposures provide the most balanced compression in terms of signal recovery. However, sensors that achieve a fully random exposure on each pixel cannot be easily realized in practice because the circuit of the sensor becomes complicated and incompatible with the sensitivity and resolution. Therefore, it is necessary to design an exposure pattern by considering the constraints enforced by hardware. In this paper, we propose a method of jointly optimizing the exposure patterns of compressive sensing and the reconstruction framework under hardware constraints. By conducting a simulation and actual experiments, we demonstrated that the proposed framework can reconstruct multiple sub-frame images with higher quality. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Compressive sensing / Video reconstruction / Deep neural network / / / / / |
| Reference Info. |
ITE Tech. Rep., vol. 42, no. 40, IST2018-59, pp. 1-2, Nov. 2018. |
| Paper # |
IST2018-59 |
| Date of Issue |
2018-11-21 (IST) |
| ISSN |
Print edition: ISSN 1342-6893 Online edition: ISSN 2424-1970 |
| Download PDF |
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| Conference Information |
| Committee |
IST |
| Conference Date |
2018-11-28 - 2018-11-28 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Tamachi Campus, TITECH |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
4th International Workshop on Image Sensors and Imaging Systems (IWISS2018) |
| Paper Information |
| Registration To |
IST |
| Conference Code |
2018-11-IST |
| Language |
English |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Joint optimization for compressive video sensing and reconstruction under hardware constraints |
| Sub Title (in English) |
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| Keyword(1) |
Compressive sensing |
| Keyword(2) |
Video reconstruction |
| Keyword(3) |
Deep neural network |
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| 1st Author's Name |
Michitaka Yoshida |
| 1st Author's Affiliation |
Kyushu University (Kyushu Univ.) |
| 2nd Author's Name |
Akihiko Torii |
| 2nd Author's Affiliation |
Tokyo Institute of Technology (Tokyo Tech) |
| 3rd Author's Name |
Masatoshi Okutomi |
| 3rd Author's Affiliation |
Tokyo Institute of Technology (Tokyo Tech) |
| 4th Author's Name |
Kenta Endo |
| 4th Author's Affiliation |
Hamamatsu Photonics K. K. (Hamamatsu Photonics K. K.) |
| 5th Author's Name |
Yukinobu Sugiyama |
| 5th Author's Affiliation |
Hamamatsu Photonics K. K. (Hamamatsu Photonics K. K.) |
| 6th Author's Name |
RIn-ichiro Taniguchi |
| 6th Author's Affiliation |
Kyushu University (Kyushu Univ.) |
| 7th Author's Name |
Hajime Nagahara |
| 7th Author's Affiliation |
Osaka University (Osaka Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2018-11-28 16:30:00 |
| Presentation Time |
90 minutes |
| Registration for |
IST |
| Paper # |
IST2018-59 |
| Volume (vol) |
vol.42 |
| Number (no) |
no.40 |
| Page |
pp.1-2 |
| #Pages |
2 |
| Date of Issue |
2018-11-21 (IST) |