TY - GEN
T1 - Automated Tracking System with Head and Tail Recognition for Time-Lapse Observation of Free-Moving C. elegans
AU - Dong, Shengnan
AU - Liu, Xiaoming
AU - Li, Pengyun
AU - Tang, Xiaoqing
AU - Liu, Dan
AU - Kojima, Masaru
AU - Huang, Qiang
AU - Arai, Tatsuo
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - In this paper, an automated tracking system with head and tail recognition for time-lapse observation of free-moving C. elegans is presented. In microscale field, active C. elegans can move out of the view easily without an automated tracking system because of the narrow field of view and rapid speed of C. elegans. In our previous works, we constructed an automated platform with 3D freedom to track centroid region of the nematode successfully. However, tracking time was not long enough to support a full time-lapse observation. Our proposed system in this study integrate the detection method in horizontal plane with depth evaluation more tightly. Tracking time and response speed have been greatly improved. Besides, we make full use of curvature calculation to make the system recognize the head and tail of C. elegans and the recognition rate can be up to 95%. The results demonstrate that the system can fully achieve automated long-term tracking of a free-living nematode and will be a nice tool for C. elegans behavioral analysis.
AB - In this paper, an automated tracking system with head and tail recognition for time-lapse observation of free-moving C. elegans is presented. In microscale field, active C. elegans can move out of the view easily without an automated tracking system because of the narrow field of view and rapid speed of C. elegans. In our previous works, we constructed an automated platform with 3D freedom to track centroid region of the nematode successfully. However, tracking time was not long enough to support a full time-lapse observation. Our proposed system in this study integrate the detection method in horizontal plane with depth evaluation more tightly. Tracking time and response speed have been greatly improved. Besides, we make full use of curvature calculation to make the system recognize the head and tail of C. elegans and the recognition rate can be up to 95%. The results demonstrate that the system can fully achieve automated long-term tracking of a free-living nematode and will be a nice tool for C. elegans behavioral analysis.
UR - http://www.scopus.com/inward/record.url?scp=85092701004&partnerID=8YFLogxK
U2 - 10.1109/ICRA40945.2020.9197546
DO - 10.1109/ICRA40945.2020.9197546
M3 - Conference contribution
AN - SCOPUS:85092701004
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 9257
EP - 9262
BT - 2020 IEEE International Conference on Robotics and Automation, ICRA 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Robotics and Automation, ICRA 2020
Y2 - 31 May 2020 through 31 August 2020
ER -