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Hand Tracking and Gesture Recognition Using Lensless Smart Sensors

The Lensless Smart Sensor (LSS) developed by Rambus, Inc. is a low-power, low-cost visual sensing technology that captures information-rich optical data in a tiny form factor using a novel approach to optical sensing. The spiral gratings of LSS diffractive grating, coupled with sophisticated computa...

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Autores principales: Abraham, Lizy, Urru, Andrea, Normani, Niccolò, Wilk, Mariusz P., Walsh, Michael, O’Flynn, Brendan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6164357/
https://www.ncbi.nlm.nih.gov/pubmed/30154305
http://dx.doi.org/10.3390/s18092834
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author Abraham, Lizy
Urru, Andrea
Normani, Niccolò
Wilk, Mariusz P.
Walsh, Michael
O’Flynn, Brendan
author_facet Abraham, Lizy
Urru, Andrea
Normani, Niccolò
Wilk, Mariusz P.
Walsh, Michael
O’Flynn, Brendan
author_sort Abraham, Lizy
collection PubMed
description The Lensless Smart Sensor (LSS) developed by Rambus, Inc. is a low-power, low-cost visual sensing technology that captures information-rich optical data in a tiny form factor using a novel approach to optical sensing. The spiral gratings of LSS diffractive grating, coupled with sophisticated computational algorithms, allow point tracking down to millimeter-level accuracy. This work is focused on developing novel algorithms for the detection of multiple points and thereby enabling hand tracking and gesture recognition using the LSS. The algorithms are formulated based on geometrical and mathematical constraints around the placement of infrared light-emitting diodes (LEDs) on the hand. The developed techniques dynamically adapt the recognition and orientation of the hand and associated gestures. A detailed accuracy analysis for both hand tracking and gesture classification as a function of LED positions is conducted to validate the performance of the system. Our results indicate that the technology is a promising approach, as the current state-of-the-art focuses on human motion tracking that requires highly complex and expensive systems. A wearable, low-power, low-cost system could make a significant impact in this field, as it does not require complex hardware or additional sensors on the tracked segments.
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spelling pubmed-61643572018-10-10 Hand Tracking and Gesture Recognition Using Lensless Smart Sensors Abraham, Lizy Urru, Andrea Normani, Niccolò Wilk, Mariusz P. Walsh, Michael O’Flynn, Brendan Sensors (Basel) Article The Lensless Smart Sensor (LSS) developed by Rambus, Inc. is a low-power, low-cost visual sensing technology that captures information-rich optical data in a tiny form factor using a novel approach to optical sensing. The spiral gratings of LSS diffractive grating, coupled with sophisticated computational algorithms, allow point tracking down to millimeter-level accuracy. This work is focused on developing novel algorithms for the detection of multiple points and thereby enabling hand tracking and gesture recognition using the LSS. The algorithms are formulated based on geometrical and mathematical constraints around the placement of infrared light-emitting diodes (LEDs) on the hand. The developed techniques dynamically adapt the recognition and orientation of the hand and associated gestures. A detailed accuracy analysis for both hand tracking and gesture classification as a function of LED positions is conducted to validate the performance of the system. Our results indicate that the technology is a promising approach, as the current state-of-the-art focuses on human motion tracking that requires highly complex and expensive systems. A wearable, low-power, low-cost system could make a significant impact in this field, as it does not require complex hardware or additional sensors on the tracked segments. MDPI 2018-08-28 /pmc/articles/PMC6164357/ /pubmed/30154305 http://dx.doi.org/10.3390/s18092834 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Abraham, Lizy
Urru, Andrea
Normani, Niccolò
Wilk, Mariusz P.
Walsh, Michael
O’Flynn, Brendan
Hand Tracking and Gesture Recognition Using Lensless Smart Sensors
title Hand Tracking and Gesture Recognition Using Lensless Smart Sensors
title_full Hand Tracking and Gesture Recognition Using Lensless Smart Sensors
title_fullStr Hand Tracking and Gesture Recognition Using Lensless Smart Sensors
title_full_unstemmed Hand Tracking and Gesture Recognition Using Lensless Smart Sensors
title_short Hand Tracking and Gesture Recognition Using Lensless Smart Sensors
title_sort hand tracking and gesture recognition using lensless smart sensors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6164357/
https://www.ncbi.nlm.nih.gov/pubmed/30154305
http://dx.doi.org/10.3390/s18092834
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