Name
Title | ||
|---|---|---|
Touch180: Finger Identification on Mobile Touchscreen using Fisheye Camera and Convolutional Neural Network. |
Abstract | ||
|---|---|---|
We present Touch180, a computer vision based solution for identifying fingers on a mobile touchscreen with a fisheye camera and deep learning algorithm. As a proof-of-concept research, this paper focused on robustness and high accuracy of finger identification. We generated a new dataset for Touch180 configuration, which is named as Fisheye180. We trained a CNN (Convolutional Neural Network)-based network utilizing touch locations as auxiliary inputs. With our novel dataset and deep learning algorithm, finger identification result shows 98.56% accuracy with VGG16 model. Our study will serve as a step stone for finger identification on a mobile touchscreen.
|
Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3266037.3266091 | UIST '18: The 31st Annual ACM Symposium on User Interface Software and Technology
Berlin
Germany
October, 2018 |
Keywords | Field | DocType |
Touchscreen,Finger Identification,Fisheye Camera,Mobile,Smart Device,Deep Learning,Convolutional Neural Network | Computer vision,Smart device,Convolutional neural network,Computer science,Touchscreen,Robustness (computer science),Human–computer interaction,Artificial intelligence,Deep learning | Conference |
ISBN | Citations | PageRank |
978-1-4503-5949-8 | 0 | 0.34 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Insu Kim | 1 | 0 | 0.34 |
| Keun-Woo Park | 2 | 0 | 1.01 |
| Youngwoo Yoon | 3 | 23 | 6.15 |
| Geehyuk Lee | 4 | 550 | 64.40 |