research-article

Differentiated Handling of Physical Scenes and Virtual Objects for Mobile Augmented Reality

Authors:

Chih-Hsuan Yen,

Tei-Wei KuoAuthors Info & Claims

2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)

Pages 1 - 8

https://doi.org/10.1145/3240765.3240798

Published: 05 November 2018 Publication History

Abstract

Mobile devices running augmented reality applications consume considerable energy for graphics-intensive workloads. This paper presents a scheme for the differentiated handling of camera-captured physical scenes and computer-generated virtual objects according to different perceptual quality metrics. We propose online algorithms and their real-time implementations to reduce energy consumption through dynamic frame rate adaptation while maintaining the visual quality required for augmented reality applications. To evaluate system efficacy, we integrate our scheme into Android and conduct extensive experiments on a commercial smartphone with various application scenarios. The results show that the proposed scheme can achieve energy savings of up to 39.1% in comparison to the native graphics system in Android while maintaining satisfactory visual quality.

References

[1]

A. Al-Shuwaili and O. Simeone. Energy-Efficient Resource Allocation for Mobile Edge Computing-Based Augmented Reality Applications. IEEE Wireless Communications Letters, 6 (3): 398–401, 2017.

[2]

A. Bartolini, M. Ruggiero and L. Benini. Visual Quality Analysis for Dynamic Backlight Scaling in LCD Systems. In Proc. of IEEE/ACM DATE, pages 1428–1433, 2009.

[3]

A.E. Kayaalp and J.L. Eckman. A Pipeline Architecture for Near Real-time Stereo Range Detection. In Mobile Robots III, volume 1007, pages 279–288, 1989.

[4]

A. Maghazeh, U.D. Bordoloi, M. Villani, P. Eles, and Z. Peng. Perception-Aware Power Management for Mobile Games via Dynamic Resolution Scaling. In Proc. of IEEE/ACM ICCAD, pages 613–620, 2015.

[5]

BT, RECOMMENDATION ITU-R. Methodology for the Subjective Assessment of the Quality of Television Pictures. 2002.

[6]

C. Hwang, S. Pushp, C. Koh, J. Yoon, Y. Liu, S. Choi, and J. Song. RAVEN: Perception-aware Optimization of Power Consumption for Mobile Games. In Proc. of ACM MobiCom, pages 422–434, 2017.

[7]

D. Kim, N. Jung, and H. Cha. Content-Centric Display Energy Management for Mobile Devices. In Proc. of IEEE/ACM DAC, pages 1–6, 2014.

[8]

H. Han, J. Yu, H. Zhu, Y. Chen, J. Yang, G. Xue, Y. Zhu, and M. Li. E3: Energy-efficient Engine for Frame Rate Adaptation on Smartphones. In Proc. of ACM Sensys, pages 15:1–15:14, 2013.

[9]

H. Kato and M. Billinghurst. Marker Tracking and HMD Calibration for a Video-based Augmented Reality Conferencing System. In Proc. of IEEE/ACM IWAR, pages 85–94, 1999.

[10]

J. Joskowicz and J.C.L. Ardao. Combining the Effects of Frame Rate, Bit Rate, Display Size and Video Content in a Parametric Video Quality Model. In Proc. of IFIP LANC, pages 4–11, 2011.

[11]

J. Klaue, B. Rathke, and A. Wolisz. EvalVid - A Framework for Video Transmission and Quality Evaluation. In Computer Performance Evaluation. Modelling Techniques and Tools, pages 255–272, 2003.

[12]

K. Debattista, K. Bugeja, S. Spina, T. Bashford-Rogers, and V. Hulusic. Frame Rate vs Resolution: A Subjective Evaluation of Spatiotemporal Perceived Quality Under Varying Computational Budgets. Computer Graphics Forum, 37 (1): 363–374, 2018.

[13]

K.T. Claypool and M. Claypool. On Frame Rate and Player Performance in First Person Shooter Games. Multimedia Systems, 13 (1): 3–17, 2007.

Digital Library

[14]

K.W. Nixon, X. Chen, and Y. Chen. Scope - Quality Retaining Display Rendering Workload Scaling Based on User-smartphone Distance. In Proc. of IEEE/ACM ICCAD, pages 1:1–1:6, 2016.

[15]

K.W. Nixon, X. Chen, H. Zhou, Y. Liu, and Y. Chen. Mobile GPU Power Consumption Reduction via Dynamic Resolution and Frame Rate Scaling. In Proc. of USENIX HotPower, pages 1–5, 2014.

[16]

D. Kim, N. Jung, and H. Cha. Content-centric Display Energy Management for Mobile Devices. In Proc. of IEEE/ACM DAC, pages 41:1–41:6, 2014.

[17]

M.H. Pinson and S. Wolf. A New Standardized Method for Objectively Measuring Video Quality. IEEE Trans. on Broadcasting, 50 (3): 312–322, 2004.

[18]

R. LiKamWa, B. Priyantha, M. Philipose, Z. Lin, and P. Bahl. Energy Characterization and Optimization of Image Sensing Toward Continuous Mobile Vision. In Proc. of ACM MobiSys, pages 69–82, 2013.

[19]

S. He, Y. Liu, and H. Zhou. Optimizing Smartphone Power Consumption Through Dynamic Resolution Scaling. In Proc. of ACM MobiCom, pages 27–39, 2015.

[20]

W.-M. Chen, S.-W. Cheng, P.-C. Hsiu, and T.-W. Kuo. A User-Centric CPU-GPU Governing Framework for 3D Games on Mobile Devices. In Proc. of IEEE/ACM ICCAD, pages 224–231, 2015.

[21]

Y. Yin, L. Xie, Y. Fan, and S. Lu. Tracking Human Motions in Photographing: A Context-Aware Energy-Saving Scheme for Smart Phones. ACM Trans. on Sensor Networks, 13 (4): 29:1–29:37, 2017.

[22]

Z. Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli. Image Quality Assessment: from Error Visibility to Structural Similarity. IEEE Trans. on Image Processing, 13 (4): 600–612, 2004.

Digital Library

[23]

Z. Wang, L. Lu, and A.C. Bovik. Video Quality Assessment Based on Structural Distortion Measurement. Signal Processing: Image Communication, 19 (2): 121–132, 2004.

Cited By

Khakpour ASánchez-Gordón MColomo-Palacios R(2020)What We Know About the Greenability of Reality Technologies: A Systematic Literature ReviewEntrepreneurship and Organizational Change10.1007/978-3-030-35415-2_5(89-113)Online publication date: 7-Jan-2020
https://doi.org/10.1007/978-3-030-35415-2_5
Kuo TChen JChang YHsiu P(2018)Real-Time Computing and the Evolution of Embedded System Designs2018 IEEE Real-Time Systems Symposium (RTSS)10.1109/RTSS.2018.00011(1-12)Online publication date: Dec-2018
https://doi.org/10.1109/RTSS.2018.00011

Index Terms

Differentiated Handling of Physical Scenes and Virtual Objects for Mobile Augmented Reality

Index terms have been assigned to the content through auto-classification.

Recommendations

Extending Virtual Reality Display Wall Environments Using Augmented Reality
SUI '19: Symposium on Spatial User Interaction

Two major form factors for virtual reality are head-mounted displays and large display environments such as CAVE®and the LCD-based successor CAVE2®. Each of these has distinct advantages and limitations based on how they’re used. This work explores ...
Speed reading on virtual reality and augmented reality
Abstract
Many virtual reality (VR) and augmented reality (AR) applications in education require speed reading. The current study aimed to explore whether the reading performance on VR and AR is different from that on traditional desktop display,...
Highlights
- We explored performance of speed reading on virtual and augmented reality.
- ...
Haptics in Augmented Reality
ICMCS '99: Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2

An augmented reality system merges synthetic sensory information into a user's perception of a three-dimensional environment. An important performance goal for an augmented reality system is that the user perceives a single seamless environment. In most ...

Comments

Information & Contributors

Information

Published In

cover image Guide Proceedings

2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)

Nov 2018

939 pages

Copyright © 2018.

Publisher

IEEE Press

Publication History

Published: 05 November 2018

Permissions

Request permissions for this article.

Request Permissions

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
103
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 10 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Khakpour ASánchez-Gordón MColomo-Palacios R(2020)What We Know About the Greenability of Reality Technologies: A Systematic Literature ReviewEntrepreneurship and Organizational Change10.1007/978-3-030-35415-2_5(89-113)Online publication date: 7-Jan-2020
https://doi.org/10.1007/978-3-030-35415-2_5
Kuo TChen JChang YHsiu P(2018)Real-Time Computing and the Evolution of Embedded System Designs2018 IEEE Real-Time Systems Symposium (RTSS)10.1109/RTSS.2018.00011(1-12)Online publication date: Dec-2018
https://doi.org/10.1109/RTSS.2018.00011

View Options

View options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents