Name
Title | ||
|---|---|---|
Preliminary Investigation Of Fine-Grained Gesture Recognition With Signal Super-Resolution |
Abstract | ||
|---|---|---|
This study investigates the feasibility of fine-grained gesture recognition using upsampled acceleration sensor data. Because the maximum sampling rate of smartwatch devices is limited by operating systems, we simulate high resolution acceleration data using a neural network from low resolution signals in order to capture distinguishing features of gestures containing high frequency components. |
Year | Venue | Field |
|---|---|---|
2018 | 2018 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS WORKSHOPS (PERCOM WORKSHOPS) | Computer vision,Microsoft Windows,Computer science,Gesture,Gesture recognition,Feature extraction,Artificial intelligence,Acceleration,Artificial neural network,Smartwatch,Image resolution,Distributed computing |
DocType | ISSN | Citations |
Conference | 2474-2503 | 0 |
PageRank | References | Authors |
0.34 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Naoya Yoshimura | 1 | 0 | 1.69 |
| Takuya Maekawa | 2 | 326 | 49.93 |
| Daichi Amagata | 3 | 43 | 13.26 |
| Takahiro Hara | 4 | 1819 | 193.85 |