Damage detector: The damage automatic detection of compartment lines using a public vehicle and a camera

Takafumi Kawasaki; Makoto Kawano; Takeshi Iwamoto; Michito Matsumoto; Takuro Yonezawa; Jin Nakazawa; Hideyuki Tokuda

doi:10.1145/3004010.3004017

Damage detector: The damage automatic detection of compartment lines using a public vehicle and a camera

Takafumi Kawasaki, Makoto Kawano, Takeshi Iwamoto, Michito Matsumoto, Takuro Yonezawa, Jin Nakazawa, Hideyuki Tokuda

Faculty of Environment and Information Studies

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In Japan, there are 1.2milion kilometers or more of the road, of which 900, 000 km of road has been paved. Paved road has been painted compartment line to separate many vehicles and driver-pedestrian. Compartment line is important for drivers and pedestrians because they can recognize for they are aware of the width of the roadway and the sidewalk by the compartment line. Therefore, municipality should inspect the ongoing compartment line but they are inspected by people so the burden for road management is big. The purpose of this research would be to automatically detect the damage of the compartment line. The image obtained from cameras, applying random forest. In this experiment, we used more than about 50, 000 of images by capturing a Walking camera and a vehicle-mounted camera. Baseline and precision comparison result, the detection of damage to compartment line, it was confirmed that the proposed method is effective.

Original language	English
Title of host publication	Adjunct Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2016
Publisher	Association for Computing Machinery
Pages	53-58
Number of pages	6
Volume	28-November-2016
ISBN (Electronic)	9781450347594
DOIs	https://doi.org/10.1145/3004010.3004017
Publication status	Published - 2016 Nov 28
Event	13th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2016 - Hiroshima, Japan Duration: 2016 Nov 28 → 2016 Dec 1

Other

Other	13th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2016
Country	Japan
City	Hiroshima
Period	16/11/28 → 16/12/1

Keywords

Camera
City management
Image processing
Machine learning
Smart sensing
Vehicle

ASJC Scopus subject areas

Human-Computer Interaction
Computer Networks and Communications
Computer Vision and Pattern Recognition
Software

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Kawasaki, T., Kawano, M., Iwamoto, T., Matsumoto, M., Yonezawa, T., Nakazawa, J., & Tokuda, H. (2016). Damage detector: The damage automatic detection of compartment lines using a public vehicle and a camera. In Adjunct Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2016 (Vol. 28-November-2016, pp. 53-58). Association for Computing Machinery. https://doi.org/10.1145/3004010.3004017

Damage detector : The damage automatic detection of compartment lines using a public vehicle and a camera. / Kawasaki, Takafumi; Kawano, Makoto; Iwamoto, Takeshi; Matsumoto, Michito; Yonezawa, Takuro; Nakazawa, Jin; Tokuda, Hideyuki.

Adjunct Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2016. Vol. 28-November-2016 Association for Computing Machinery, 2016. p. 53-58.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kawasaki, T, Kawano, M, Iwamoto, T, Matsumoto, M, Yonezawa, T, Nakazawa, J & Tokuda, H 2016, Damage detector: The damage automatic detection of compartment lines using a public vehicle and a camera. in Adjunct Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2016. vol. 28-November-2016, Association for Computing Machinery, pp. 53-58, 13th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2016, Hiroshima, Japan, 16/11/28. https://doi.org/10.1145/3004010.3004017

Kawasaki T, Kawano M, Iwamoto T, Matsumoto M, Yonezawa T, Nakazawa J et al. Damage detector: The damage automatic detection of compartment lines using a public vehicle and a camera. In Adjunct Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2016. Vol. 28-November-2016. Association for Computing Machinery. 2016. p. 53-58 https://doi.org/10.1145/3004010.3004017

Kawasaki, Takafumi ; Kawano, Makoto ; Iwamoto, Takeshi ; Matsumoto, Michito ; Yonezawa, Takuro ; Nakazawa, Jin ; Tokuda, Hideyuki. / Damage detector : The damage automatic detection of compartment lines using a public vehicle and a camera. Adjunct Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2016. Vol. 28-November-2016 Association for Computing Machinery, 2016. pp. 53-58

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abstract = "In Japan, there are 1.2milion kilometers or more of the road, of which 900, 000 km of road has been paved. Paved road has been painted compartment line to separate many vehicles and driver-pedestrian. Compartment line is important for drivers and pedestrians because they can recognize for they are aware of the width of the roadway and the sidewalk by the compartment line. Therefore, municipality should inspect the ongoing compartment line but they are inspected by people so the burden for road management is big. The purpose of this research would be to automatically detect the damage of the compartment line. The image obtained from cameras, applying random forest. In this experiment, we used more than about 50, 000 of images by capturing a Walking camera and a vehicle-mounted camera. Baseline and precision comparison result, the detection of damage to compartment line, it was confirmed that the proposed method is effective.",

keywords = "Camera, City management, Image processing, Machine learning, Smart sensing, Vehicle",

author = "Takafumi Kawasaki and Makoto Kawano and Takeshi Iwamoto and Michito Matsumoto and Takuro Yonezawa and Jin Nakazawa and Hideyuki Tokuda",

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AU - Kawasaki, Takafumi

AU - Kawano, Makoto

AU - Iwamoto, Takeshi

AU - Matsumoto, Michito

AU - Yonezawa, Takuro

AU - Nakazawa, Jin

AU - Tokuda, Hideyuki

PY - 2016/11/28

Y1 - 2016/11/28

N2 - In Japan, there are 1.2milion kilometers or more of the road, of which 900, 000 km of road has been paved. Paved road has been painted compartment line to separate many vehicles and driver-pedestrian. Compartment line is important for drivers and pedestrians because they can recognize for they are aware of the width of the roadway and the sidewalk by the compartment line. Therefore, municipality should inspect the ongoing compartment line but they are inspected by people so the burden for road management is big. The purpose of this research would be to automatically detect the damage of the compartment line. The image obtained from cameras, applying random forest. In this experiment, we used more than about 50, 000 of images by capturing a Walking camera and a vehicle-mounted camera. Baseline and precision comparison result, the detection of damage to compartment line, it was confirmed that the proposed method is effective.

AB - In Japan, there are 1.2milion kilometers or more of the road, of which 900, 000 km of road has been paved. Paved road has been painted compartment line to separate many vehicles and driver-pedestrian. Compartment line is important for drivers and pedestrians because they can recognize for they are aware of the width of the roadway and the sidewalk by the compartment line. Therefore, municipality should inspect the ongoing compartment line but they are inspected by people so the burden for road management is big. The purpose of this research would be to automatically detect the damage of the compartment line. The image obtained from cameras, applying random forest. In this experiment, we used more than about 50, 000 of images by capturing a Walking camera and a vehicle-mounted camera. Baseline and precision comparison result, the detection of damage to compartment line, it was confirmed that the proposed method is effective.

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KW - City management

KW - Image processing

KW - Machine learning

KW - Smart sensing

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ER -

Damage detector: The damage automatic detection of compartment lines using a public vehicle and a camera

Abstract

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Keywords

ASJC Scopus subject areas

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