helpResearch questionInput Recognition, Touch Modeling, and Interaction Decoding Methods
How can deep learning identify whether users hold phones with left hand, right hand, or both hands?Sensing, Recognition, and Prediction Methods / Input Recognition, Touch Modeling, and Interaction Decoding Methods
How can deep learning identify whether users hold phones with left hand, right hand, or both hands?
Similar questions
helpResearch questionInput Recognition, Touch Modeling, and Interaction Decoding Methods
How can magnetic-field-assisted techniques overcome clock drift between wireless earbuds and smart devices?helpResearch questionInput Recognition, Touch Modeling, and Interaction Decoding Methods
Can combining magnetic fields and acoustic sensing improve the accuracy and stability of real-time tracking with wireless earbuds?helpResearch questionInput Recognition, Touch Modeling, and Interaction Decoding Methods
Can the MagSound system enable high-precision applications such as handwriting recognition and expand wireless earbud interaction potential?helpResearch questionInput Recognition, Touch Modeling, and Interaction Decoding Methods
Can a standard smartphone front camera detect users' phone-holding mode in real time using only body silhouette images?helpResearch questionInput Recognition, Touch Modeling, and Interaction Decoding Methods
How can hand-mode recognition accuracy and applicability be improved without additional hardware?helpResearch questionInput Recognition, Touch Modeling, and Interaction Decoding Methods
How do users perform on preventing accidental touch keyboard input?Related papers
UbiComp 2023
MagSound: Magnetic Field Assisted Wireless Earphone Tracking
Lihao Wang, Wei Wang, Haipeng Dai
UIST 2021
HandyTrak: Recognizing the Holding Hand on a Commodity Smartphone from Body Silhouette Images
Hyunchul Lim, David Lin, Jessica Tweneboah
UIST 2021
TypeBoard: Identifying Unintentional Touch on Pressure-Sensitive Touchscreen Keyboards
Yizheng Gu, Chun Yu, Xuanzhong Chen