Pupil Detection for Augmented and Virtual Reality based on Images with Reduced Bit Depths

Gernot Fiala; Zhenyu Ye; Christian Steger

doi:10.1109/SAS54819.2022.9881378

Pupil Detection for Augmented and Virtual Reality based on Images with Reduced Bit Depths

Gernot Fiala, Zhenyu Ye, Christian Steger

Institut für Technische Informatik (4480)

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Abstract

For future augmented reality (AR) and virtual
reality (VR) applications, several different kinds of sensors will
be used. These sensors, to give some examples, are used for
gesture recognition, head pose tracking and pupil tracking. All
these sensors send data to a host platform, where the data must
be processed in real-time. This requires high processing power
which leads to higher energy consumption. To lower the energy
consumption, optimizations of the image processing system are
necessary. This paper investigates pupil detection for AR/VR
applications based on images with reduced bit depths. It shows
that images with reduced bit depths even down to 3 or 2 bits
can be used for pupil detection, with almost the same average
detection rate. Reduced bit depths of an image reduces the
memory foot-print, which allows to perform in-sensor processing
for future image sensors and provides the foundation for future
in-sensor processing architectures.

Originalsprache	englisch
Titel	2022 IEEE Sensors Applications Symposium (SAS 2022)
Herausgeber (Verlag)	IEEE Xplore
Seitenumfang	5
ISBN (elektronisch)	978-1-6654-0981-0
ISBN (Print)	978-1-6654-0982-7
DOIs	https://doi.org/10.1109/SAS54819.2022.9881378
Publikationsstatus	Veröffentlicht - 12 Sept. 2022
Veranstaltung	17th IEEE Sensors Applications Symposium: SAS 2022 - Hybrider Event, Sundsvall, Schweden Dauer: 1 Aug. 2022 → 3 Aug. 2022

Konferenz

Konferenz	17th IEEE Sensors Applications Symposium
Kurztitel	SAS 2022
Land/Gebiet	Schweden
Ort	Hybrider Event, Sundsvall
Zeitraum	1/08/22 → 3/08/22

Schlagwörter

pupil detection
smart image sensor
augmented reality
virtual reality
bit depth
in-sensor processing

ASJC Scopus subject areas

Informatik (insg.)

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

Zugriff auf Dokument

10.1109/SAS54819.2022.9881378

Andere Dateien und Links

2 Konferenz oder Fachtagung (Teilnahme an/Organisation von)
1 Vortrag bei Konferenz oder Fachtagung

17th IEEE Sensors Applications Symposium
Gernot Fiala (Teilnehmer/-in)
1 Aug. 2022 → 3 Aug. 2022
Aktivität: Teilnahme an / Organisation von › Konferenz oder Fachtagung (Teilnahme an/Organisation von)
Pupil Detection for Augmented and Virtual Reality based on Images with Reduced Bit Depths
Gernot Fiala (Redner/in)
1 Aug. 2022 → 3 Aug. 2022
Aktivität: Vortrag oder Präsentation › Vortrag bei Konferenz oder Fachtagung › Science to science
17th IEEE Sensors Applications Symposium
Gernot Fiala (Teilnehmer/-in)
1 Aug. 2022 → 3 Aug. 2022
Aktivität: Teilnahme an / Organisation von › Konferenz oder Fachtagung (Teilnahme an/Organisation von)

Dieses zitieren

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title = "Pupil Detection for Augmented and Virtual Reality based on Images with Reduced Bit Depths",

abstract = "For future augmented reality (AR) and virtual reality (VR) applications, several different kinds of sensors will be used. These sensors, to give some examples, are used for gesture recognition, head pose tracking and pupil tracking. All these sensors send data to a host platform, where the data must be processed in real-time. This requires high processing power which leads to higher energy consumption. To lower the energy consumption, optimizations of the image processing system are necessary. This paper investigates pupil detection for AR/VR applications based on images with reduced bit depths. It shows that images with reduced bit depths even down to 3 or 2 bits can be used for pupil detection, with almost the same average detection rate. Reduced bit depths of an image reduces the memory foot-print, which allows to perform in-sensor processing for future image sensors and provides the foundation for future in-sensor processing architectures.",

keywords = "pupil detection, smart image sensor, augmented reality, virtual reality, bit depth, in-sensor processing",

author = "Gernot Fiala and Zhenyu Ye and Christian Steger",

year = "2022",

month = sep,

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doi = "10.1109/SAS54819.2022.9881378",

language = "English",

isbn = "978-1-6654-0982-7",

booktitle = "2022 IEEE Sensors Applications Symposium (SAS 2022)",

publisher = "IEEE Xplore",

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T1 - Pupil Detection for Augmented and Virtual Reality based on Images with Reduced Bit Depths

AU - Fiala, Gernot

AU - Ye, Zhenyu

AU - Steger, Christian

PY - 2022/9/12

Y1 - 2022/9/12

N2 - For future augmented reality (AR) and virtual reality (VR) applications, several different kinds of sensors will be used. These sensors, to give some examples, are used for gesture recognition, head pose tracking and pupil tracking. All these sensors send data to a host platform, where the data must be processed in real-time. This requires high processing power which leads to higher energy consumption. To lower the energy consumption, optimizations of the image processing system are necessary. This paper investigates pupil detection for AR/VR applications based on images with reduced bit depths. It shows that images with reduced bit depths even down to 3 or 2 bits can be used for pupil detection, with almost the same average detection rate. Reduced bit depths of an image reduces the memory foot-print, which allows to perform in-sensor processing for future image sensors and provides the foundation for future in-sensor processing architectures.

AB - For future augmented reality (AR) and virtual reality (VR) applications, several different kinds of sensors will be used. These sensors, to give some examples, are used for gesture recognition, head pose tracking and pupil tracking. All these sensors send data to a host platform, where the data must be processed in real-time. This requires high processing power which leads to higher energy consumption. To lower the energy consumption, optimizations of the image processing system are necessary. This paper investigates pupil detection for AR/VR applications based on images with reduced bit depths. It shows that images with reduced bit depths even down to 3 or 2 bits can be used for pupil detection, with almost the same average detection rate. Reduced bit depths of an image reduces the memory foot-print, which allows to perform in-sensor processing for future image sensors and provides the foundation for future in-sensor processing architectures.

KW - pupil detection

KW - smart image sensor

KW - augmented reality

KW - virtual reality

KW - bit depth

KW - in-sensor processing

UR - https://ieeexplore.ieee.org/document/9881378

UR - http://www.scopus.com/inward/record.url?scp=85139105189&partnerID=8YFLogxK

U2 - 10.1109/SAS54819.2022.9881378

DO - 10.1109/SAS54819.2022.9881378

M3 - Conference paper

SN - 978-1-6654-0982-7

BT - 2022 IEEE Sensors Applications Symposium (SAS 2022)

PB - IEEE Xplore

T2 - 17th IEEE Sensors Applications Symposium

Y2 - 1 August 2022 through 3 August 2022

ER -

Pupil Detection for Augmented and Virtual Reality based on Images with Reduced Bit Depths

Abstract

Konferenz

Schlagwörter

ASJC Scopus subject areas

UN SDGs

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Andere Dateien und Links

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Aktivitäten

17th IEEE Sensors Applications Symposium