Touch180: Finger Identification on Mobile Touchscreen using Fisheye Camera and Convolutional Neural Network

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.

Kim, I., Park, K., Yoon Y., & Lee, G. "Touch180: Finger Identification on Mobile Touchscreen using Fisheye Camera and Convolutional Neural Network." The 31st Annual ACM Symposium on User Interface Software and Technology Adjunct Proceedings. ACM, 2018.

Related Document Link : https://doi.org/10.1145/3266037.3266091