Title
RF-Brush: 3D Human-Computer Interaction via Linear Tag Array
Abstract
Nowadays, novel approaches of 3D human-computer interaction have enabled the capability of manipulating in the 3D space rather than 2D space. For example, Microsoft Surface Pen leverages the embedded sensors to sense the 3D manipulations, such as inclining the pen to get bolder handwriting. In this paper, we propose RF-Brush, a battery-free and light-weight solution for 3D human-computer interaction based on RFID, by simply attaching a linear RFID tag array onto the linear shaped object like a brush. RF-Brush senses the 3D orientation and 2D movement of the linear shaped object, when the human subject is drawing with this object in the 3D space. Here, the 3D orientation refers to the relative orientation of the linear shaped object to the operating plane, whereas the 2D movement refers to the moving trace in the 2D operating plane. In this way, we are able to transform an ordinary linear shaped object like a brush or pen to an intelligent HCI device. Particularly, we build two geometric models to depict the relationship between the RF-signal and the 3D orientation as well as 2D movement, respectively. Based on the geometric model, we propose the linear tag array-based HCI solution, implemented a prototype system, and evaluated the performance in real environment. The experiments show that RF-Brush achieves an average error of 5.7° and 8.6° of elevation and azimuthal angle, respectively, and an average error of 3.8cm and 4.2cm in movement tracking along X-axis and Y-axis, respectively. Moreover, RF-Brush achieves 89% in letter recognition accuracy.
Year
DOI
Venue
2018
10.1109/MASS.2018.00051
2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)
Keywords
Field
DocType
RFID,Human Computer Interaction,Tag Array
Movement tracking,Computer vision,Handwriting,Computer science,Geometric modeling,Letter recognition,Brush,Azimuth,Artificial intelligence,Elevation,Distributed computing
Conference
ISSN
ISBN
Citations 
2155-6806
978-1-5386-5581-8
0
PageRank 
References 
Authors
0.34
11
5
Name
Order
Citations
PageRank
Yinyin Gong141.41
Lei Xie228334.16
Chuyu Wang3518.87
Yanling Bu4154.73
Sanglu Lu51380144.07