TY - GEN
T1 - Estimation of the Pressing Force from Finger Image by Using Neural Network
AU - Inoue, Yoshinori
AU - Makino, Yasutoshi
AU - Shinoda, Hiroyuki
N1 - Publisher Copyright:
© Springer International Publishing AG, part of Springer Nature 2018.
PY - 2018
Y1 - 2018
N2 - In this paper, we propose a method that estimates contact force to hard surface from a single visual image of a finger by using a neural network. In general, it is hard to estimate applied force to hard object only from visual images as the object surface hardly moves. In this paper, we focus on the human side. When persons push an object, posture of hand reflects how hard he/she pushes the surface. Observation of human body condition will tell the haptic information. We used the Convolutional Neural Network to make the system learn the relationship between the applied force and the finger posture. We created a neural network model individually. The evaluation result shows that a root mean square error from the actual force is approximately 0.5Â N for the best case, which is 2.5% to the dynamic range (0–20Â N) of applied force.
AB - In this paper, we propose a method that estimates contact force to hard surface from a single visual image of a finger by using a neural network. In general, it is hard to estimate applied force to hard object only from visual images as the object surface hardly moves. In this paper, we focus on the human side. When persons push an object, posture of hand reflects how hard he/she pushes the surface. Observation of human body condition will tell the haptic information. We used the Convolutional Neural Network to make the system learn the relationship between the applied force and the finger posture. We created a neural network model individually. The evaluation result shows that a root mean square error from the actual force is approximately 0.5Â N for the best case, which is 2.5% to the dynamic range (0–20Â N) of applied force.
UR - https://www.scopus.com/pages/publications/85048656251
UR - https://www.scopus.com/pages/publications/85048656251#tab=citedBy
U2 - 10.1007/978-3-319-93399-3_5
DO - 10.1007/978-3-319-93399-3_5
M3 - Conference contribution
AN - SCOPUS:85048656251
SN - 9783319933986
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 46
EP - 57
BT - Haptics
A2 - Prattichizzo, Domenico
A2 - Ruffaldi, Emanuele
A2 - Frisoli, Antonio
A2 - Shinoda, Hiroyuki
A2 - Tan, Hong Z.
PB - Springer Verlag
T2 - 11th International Conference on Haptics: Science, Technology, and Applications, EuroHaptics 2018
Y2 - 13 June 2018 through 16 June 2018
ER -