Abstract
This paper shows a novel method to extract hand Representative Point (RP) based on 2-dimensional laser range scanner for hand motion estimation on projecting system. Image-projecting Desktop Arm Trainer (IDAT) is a projecting system for hand-eye coordination training, in which a projector displays an exercise screen on the desktop, and a laser range scanner detects trainee's hand motion. To realize multi-user HMI and expand more entertainment functions in IDAT system, an Air Hockey application was developed in which the hand RP requires a high precision. To generate hand RP precisely, we proposed our method in two parts to solve the data error problem and changeable hand contour problem. In part one, a data modifier is proposed and a sub-experiment is carried out to establish a modifying function for correcting sensor original data. In part two, we proposed three RP algorithms and carried out an evaluation experiment to estimate the reliability of three algorithms under different conditions. From the result, we get the most reliable algorithm corresponding to different situations in which the error of hand RP is less than 9.6 mm.
| Original language | English |
|---|---|
| Title of host publication | 2015 IEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO 2015 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 2139-2144 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781467396745 |
| DOIs | |
| Publication status | Published - 2016 Feb 24 |
| Event | IEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO 2015 - Zhuhai, China Duration: 2015 Dec 6 → 2015 Dec 9 |
Other
| Other | IEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO 2015 |
|---|---|
| Country | China |
| City | Zhuhai |
| Period | 15/12/6 → 15/12/9 |
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ASJC Scopus subject areas
- Artificial Intelligence
- Hardware and Architecture
- Control and Systems Engineering
Cite this
Extraction of representative point from hand contour data based on laser range scanner for hand motion estimation. / Dai, Chuankai; Matsumaru, Takafumi.
2015 IEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO 2015. Institute of Electrical and Electronics Engineers Inc., 2016. p. 2139-2144 7419090.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Extraction of representative point from hand contour data based on laser range scanner for hand motion estimation
AU - Dai, Chuankai
AU - Matsumaru, Takafumi
PY - 2016/2/24
Y1 - 2016/2/24
N2 - This paper shows a novel method to extract hand Representative Point (RP) based on 2-dimensional laser range scanner for hand motion estimation on projecting system. Image-projecting Desktop Arm Trainer (IDAT) is a projecting system for hand-eye coordination training, in which a projector displays an exercise screen on the desktop, and a laser range scanner detects trainee's hand motion. To realize multi-user HMI and expand more entertainment functions in IDAT system, an Air Hockey application was developed in which the hand RP requires a high precision. To generate hand RP precisely, we proposed our method in two parts to solve the data error problem and changeable hand contour problem. In part one, a data modifier is proposed and a sub-experiment is carried out to establish a modifying function for correcting sensor original data. In part two, we proposed three RP algorithms and carried out an evaluation experiment to estimate the reliability of three algorithms under different conditions. From the result, we get the most reliable algorithm corresponding to different situations in which the error of hand RP is less than 9.6 mm.
AB - This paper shows a novel method to extract hand Representative Point (RP) based on 2-dimensional laser range scanner for hand motion estimation on projecting system. Image-projecting Desktop Arm Trainer (IDAT) is a projecting system for hand-eye coordination training, in which a projector displays an exercise screen on the desktop, and a laser range scanner detects trainee's hand motion. To realize multi-user HMI and expand more entertainment functions in IDAT system, an Air Hockey application was developed in which the hand RP requires a high precision. To generate hand RP precisely, we proposed our method in two parts to solve the data error problem and changeable hand contour problem. In part one, a data modifier is proposed and a sub-experiment is carried out to establish a modifying function for correcting sensor original data. In part two, we proposed three RP algorithms and carried out an evaluation experiment to estimate the reliability of three algorithms under different conditions. From the result, we get the most reliable algorithm corresponding to different situations in which the error of hand RP is less than 9.6 mm.
UR - http://www.scopus.com/inward/record.url?scp=84964528933&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84964528933&partnerID=8YFLogxK
U2 - 10.1109/ROBIO.2015.7419090
DO - 10.1109/ROBIO.2015.7419090
M3 - Conference contribution
SP - 2139
EP - 2144
BT - 2015 IEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO 2015
PB - Institute of Electrical and Electronics Engineers Inc.
ER -