Paper
6 March 2013 Shape recognition for capacitive touch display
Author Affiliations +
Proceedings Volume 8661, Image Processing: Machine Vision Applications VI; 86610R (2013) https://doi.org/10.1117/12.2007578
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States
Abstract
In this paper we present a technique to classify five common classes of shapes acquired with a capacitive touch display: finger, ear, cheek, hand hold, half ear-half cheek. The need of algorithms able to discriminate among the aforementioned shapes comes from the growing diffusion of touch screen based consumer devices (e.g. smartphones, tablet, etc.). In this context, detection and the recognition of fingers are fundamental tasks in many touch based user applications (e.g., mobile games). Shape recognition algorithms are also extremely useful to identify accidental touches in order to avoid involuntary activation of the device functionalities (e.g., accidental calls). Our solution makes use of simple descriptors designed to capture discriminative information of the considered classes of shapes. The recognition is performed through a decision tree based approach whose parameters are learned on a set of labeled samples. Experimental results demonstrate that the proposed solution achieves good recognition accuracy.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
I. Guarneri, A. Capra, G. M. Farinella, and S. Battiato "Shape recognition for capacitive touch display", Proc. SPIE 8661, Image Processing: Machine Vision Applications VI, 86610R (6 March 2013); https://doi.org/10.1117/12.2007578
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Ear

Detection and tracking algorithms

Shape analysis

Signal to noise ratio

Capacitance

Electrodes

Diffusion

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