Integration of visual information processing system for spatial perception by motion stereo vision
Project/Area Number |
15K18044
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Research Category |
Grant-in-Aid for Young Scientists (B)
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Allocation Type | Multi-year Fund |
Research Field |
Electron device/Electronic equipment
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Research Institution | Tohoku University |
Principal Investigator |
Akima Hisanao 東北大学, 電気通信研究所, 助教 (40707840)
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Research Collaborator |
KAWAKAMI Susumu
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Project Period (FY) |
2015-04-01 – 2018-03-31
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Project Status |
Completed (Fiscal Year 2017)
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Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2017: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2016: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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Keywords | 運動立体視 / 空間認識 / LSI / 神経回路網モデル / Hough変換 / 視覚情報処理 |
Outline of Final Research Achievements |
Spatial perception is indispensable to achieve such as self-driving cars and autonomous mobile robots. The purpose of this research is to construct a spatial perception system with high power performance ratio by developing an LSI for the neural network model of motion stereo vision in which spatial perception is performed based on visual motion. The optimal virtual connection schemes were adopted for each stage of the model to implement a huge number of neural connections into a limited chip area. A real-time spatial perception system was also developed for actual environment testing. As a result, the optical flow corresponding to an approaching object was successfully detected in 30 frames per second, and the power performance ratio of more than 100 times higher than a conventional CPU was achieved.
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Report
(4 results)
Research Products
(38 results)
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[Journal Article] CMOS Majority Circuit with Large Fan-In2016
Author(s)
H. Akima, Y. Katayama, M. Sakuraba, K. Nakajima, J. Madrenas, and S.Sato
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Journal Title
IEICE Transactions on Electronics
Volume: E99.C
Issue: 9
Pages: 1056-1064
DOI
NAID
ISSN
0916-8524, 1745-1353
Related Report
Peer Reviewed / Int'l Joint Research / Acknowledgement Compliant
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[Presentation] スピン軌道トルク磁気メモリデバイスを用いた自己連想記憶2017
Author(s)
秋間学尚, Borders William, 深見俊輔, 守谷哲, 栗原祥太, Kurenkov Alexander, 下橋亮太, 堀尾喜彦, 佐藤茂雄, 大野英男
Organizer
2017年 電子情報通信学会 総合大会
Place of Presentation
名城大学
Year and Date
2017-03-22
Related Report
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[Presentation] Learning Method for a Quantum Bit Network2016
Author(s)
Y. Osakabe, S. Sato, M. Kinjo, K. Nakajima, H. Akima, and M. Sakuraba
Organizer
25th International Conference on Artificial Neural Networks (ICANN 2016)
Place of Presentation
Barcelona, Spain
Year and Date
2016-09-06
Related Report
Int'l Joint Research
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