DeepCounter: Using deep learning to count garbage bags

Kazuhiro Mikami; Yin Chen; Jin Nakazawa; Yasuhiro Iida; Yasunari Kishimoto; Yu Oya

doi:10.1109/RTCSA.2018.00010

DeepCounter: Using deep learning to count garbage bags

Kazuhiro Mikami, Yin Chen, Jin Nakazawa, Yasuhiro Iida, Yasunari Kishimoto, Yu Oya

環境情報学部

研究成果: Conference contribution

10 被引用数 (Scopus)

抄録

This paper proposes DeepCounter, an automotive sensing system where deep learning based image processing technology is used to automatically count the number of collected garbage bags from the video taken by a camera mounted on the rear of a garbage truck in order to sense a fine-grain spatio-temporal distribution on the amount of disposed garbage in cities that is envisioned to be helpful to develop novel applications related to garbage collection there. A prototype system is implemented on a GPU-integrated signal-board computer. A detection-tracking-counting (DTC) algorithm is developed and implemented based on the single shot multibox detector (SSD), a well-known real-time object detection algorithm. Experimental evaluation validates the feasibility of the proposed approach using video of realistic garbage collection in Fujisawa city, Japan.

本文言語	English
ホスト出版物のタイトル	Proceedings - 2018 IEEE 24th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018
出版社	Institute of Electrical and Electronics Engineers Inc.
ページ	1-10
ページ数	10
ISBN（電子版）	9781538677599
DOI	https://doi.org/10.1109/RTCSA.2018.00010
出版ステータス	Published - 2019 1月 9
イベント	24th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018 - Hakodate, Japan 継続期間: 2018 8月 29 → 2018 8月 31

出版物シリーズ

名前	Proceedings - 2018 IEEE 24th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018

Conference

Conference	24th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018
国/地域	Japan
City	Hakodate
Period	18/8/29 → 18/8/31

ASJC Scopus subject areas

人工知能
コンピュータネットワークおよび通信
コンピュータサイエンスの応用

UN SDG

この成果は、次の持続可能な開発目標に貢献しています

文献へのアクセス

10.1109/RTCSA.2018.00010

他のファイルとリンク

引用スタイル

Mikami, K., Chen, Y., Nakazawa, J., Iida, Y., Kishimoto, Y., & Oya, Y. (2019). DeepCounter: Using deep learning to count garbage bags. In Proceedings - 2018 IEEE 24th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018 (pp. 1-10). [8607228] (Proceedings - 2018 IEEE 24th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RTCSA.2018.00010

DeepCounter: Using deep learning to count garbage bags. / Mikami, Kazuhiro; Chen, Yin; Nakazawa, Jin その他.
Proceedings - 2018 IEEE 24th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1-10 8607228 (Proceedings - 2018 IEEE 24th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018).

研究成果: Conference contribution

Mikami, K, Chen, Y, Nakazawa, J, Iida, Y, Kishimoto, Y & Oya, Y 2019, DeepCounter: Using deep learning to count garbage bags. in Proceedings - 2018 IEEE 24th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018., 8607228, Proceedings - 2018 IEEE 24th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018, Institute of Electrical and Electronics Engineers Inc., pp. 1-10, 24th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018, Hakodate, Japan, 18/8/29. https://doi.org/10.1109/RTCSA.2018.00010

Mikami K, Chen Y, Nakazawa J, Iida Y, Kishimoto Y, Oya Y. DeepCounter: Using deep learning to count garbage bags. In Proceedings - 2018 IEEE 24th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1-10. 8607228. (Proceedings - 2018 IEEE 24th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018). doi: 10.1109/RTCSA.2018.00010

Mikami, Kazuhiro ; Chen, Yin ; Nakazawa, Jin その他. / DeepCounter : Using deep learning to count garbage bags. Proceedings - 2018 IEEE 24th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1-10 (Proceedings - 2018 IEEE 24th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018).

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abstract = "This paper proposes DeepCounter, an automotive sensing system where deep learning based image processing technology is used to automatically count the number of collected garbage bags from the video taken by a camera mounted on the rear of a garbage truck in order to sense a fine-grain spatio-temporal distribution on the amount of disposed garbage in cities that is envisioned to be helpful to develop novel applications related to garbage collection there. A prototype system is implemented on a GPU-integrated signal-board computer. A detection-tracking-counting (DTC) algorithm is developed and implemented based on the single shot multibox detector (SSD), a well-known real-time object detection algorithm. Experimental evaluation validates the feasibility of the proposed approach using video of realistic garbage collection in Fujisawa city, Japan.",

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DeepCounter: Using deep learning to count garbage bags

抄録

出版物シリーズ

Conference

ASJC Scopus subject areas

UN SDG

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