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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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2018-08, Vol.18 (9), p.2834
Main Authors: Abraham, Lizy, Urru, Andrea, Normani, Niccolò, Wilk, Mariusz P, Walsh, Michael, O'Flynn, Brendan
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Artificial intelligence
Calibration
Form factors
Gesture recognition
Gestures
Gratings (spectra)
Hand
Hands
Human motion
Humans
Infrared LEDs
Infrared radiation
International conferences
Kalman filters
latency
Low cost
LSS
Monitoring, Physiologic - economics
Monitoring, Physiologic - instrumentation
Monitoring, Physiologic - methods
Movement
Organic light emitting diodes
Repeatability
RMSE
Sensors
Smart sensors
State of the art
Temporal Noise
Tracking
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Summary: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.
ISSN:1424-8220
1424-8220
DOI:10.3390/s18092834