抄録
The Tsukuba Challenge is a competition, in which autonomous mobile robots run on a route set on a public road under a real environment. Their task includes not only simple running but also finding multiple specific persons at the same time. This study proposes a method that would realize person searching. While many person-searching algorithms use a laser sensor and a camera in combination, our method only uses an omnidirectional camera. The search target is detected using a convolutional neural network (CNN) that performs a classification of the search target. Training a CNN requires a great amount of data for which pseudo images created by composition are used. Our method is implemented in an autonomous mobile robot, and its performance has been verified in the Tsukuba Challenge 2017.
| 元の言語 | English |
|---|---|
| ページ（範囲） | 540-551 |
| ページ数 | 12 |
| ジャーナル | Journal of Robotics and Mechatronics |
| 巻 | 30 |
| 発行部数 | 4 |
| DOI | |
| 出版物ステータス | Published - 2018 8 1 |
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ASJC Scopus subject areas
- Computer Science(all)
- Electrical and Electronic Engineering
これを引用
Person searching through an omnidirectional camera using CNN in the tsukuba challenge. / Nakamura, Shingo; Hasegawa, Tadahiro; Hiraoka, Tsubasa; Ochiai, Yoshinori; Yuta, Shinichi.
：: Journal of Robotics and Mechatronics, 巻 30, 番号 4, 01.08.2018, p. 540-551.研究成果: Article
}
TY - JOUR
T1 - Person searching through an omnidirectional camera using CNN in the tsukuba challenge
AU - Nakamura, Shingo
AU - Hasegawa, Tadahiro
AU - Hiraoka, Tsubasa
AU - Ochiai, Yoshinori
AU - Yuta, Shinichi
PY - 2018/8/1
Y1 - 2018/8/1
N2 - The Tsukuba Challenge is a competition, in which autonomous mobile robots run on a route set on a public road under a real environment. Their task includes not only simple running but also finding multiple specific persons at the same time. This study proposes a method that would realize person searching. While many person-searching algorithms use a laser sensor and a camera in combination, our method only uses an omnidirectional camera. The search target is detected using a convolutional neural network (CNN) that performs a classification of the search target. Training a CNN requires a great amount of data for which pseudo images created by composition are used. Our method is implemented in an autonomous mobile robot, and its performance has been verified in the Tsukuba Challenge 2017.
AB - The Tsukuba Challenge is a competition, in which autonomous mobile robots run on a route set on a public road under a real environment. Their task includes not only simple running but also finding multiple specific persons at the same time. This study proposes a method that would realize person searching. While many person-searching algorithms use a laser sensor and a camera in combination, our method only uses an omnidirectional camera. The search target is detected using a convolutional neural network (CNN) that performs a classification of the search target. Training a CNN requires a great amount of data for which pseudo images created by composition are used. Our method is implemented in an autonomous mobile robot, and its performance has been verified in the Tsukuba Challenge 2017.
KW - Convolutional neural networks
KW - Omnidirectional camera
KW - Person searching
KW - Tsukuba challenge
UR - http://www.scopus.com/inward/record.url?scp=85052198459&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85052198459&partnerID=8YFLogxK
U2 - 10.20965/jrm.2018.p0540
DO - 10.20965/jrm.2018.p0540
M3 - Article
AN - SCOPUS:85052198459
VL - 30
SP - 540
EP - 551
JO - Journal of Robotics and Mechatronics
JF - Journal of Robotics and Mechatronics
SN - 0915-3942
IS - 4
ER -