Name
Title | ||
|---|---|---|
Classification Method of Rubbing Haptic Information Using Convolutional Neural Network. |
Abstract | ||
|---|---|---|
In previous research, we proposed a method to collect accelerations in daily haptic behaviors using a ZigBee-based microcomputer. However, the method for classifying the collected data was not sufficiently implemented. We therefore propose applying collected data to classify rubbing haptic information. In this paper, we implemented a classification approach for haptic information collected by our method. We used a convolutional neural network (CNN) to classify the information. We performed a classification experiment in which the CNN classified 18 types of information, 93.2% on average. We also performed an experiment to classify rubbed objects in real-time. The CNN was able to classify five types of objects, about 67.7% on average. |
Year | Venue | Field |
|---|---|---|
2018 | HCI | Pattern recognition,Computer science,Convolutional neural network,Rubbing,Artificial intelligence,Microcomputer,Haptic technology |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
4 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shotaro Agatsuma | 1 | 0 | 0.68 |
| Shinji Nakagawa | 2 | 0 | 0.34 |
| Tomoyoshi Ono | 3 | 0 | 0.34 |
| Satoshi Saga | 4 | 68 | 11.90 |
| Simona Vasilache | 5 | 1 | 2.99 |
| Shin Takahashi | 6 | 191 | 29.40 |