LSIM: Ultra lightweight similarity measurement for mobile graphics applications

Yu Chuan Chang, Wei Ming Chen, Pi Cheng Hsiu, Yen-Yu Lin, Tei Wei Kuo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Perceptual similarity measurement allows mobile applications to eliminate unnecessary computations without compromising visual experience. Existing pixel-wise measures incur significant overhead with increasing display resolutions and frame rates. This paper presents an ultra lightweight similarity measure called LSIM, which assesses the similarity between frames based on the transformation matrices of graphics objects. To evaluate its efficacy, we integrate LSIM into the Open Graphics Library and conduct experiments on an Android smartphone with various mobile 3D games. The results show that LSIM is highly correlated with the most widely used pixel-wise measure SSIM, yet three to five orders of magnitude faster. We also apply LSIM to a CPU-GPU governor to suppress the rendering of similar frames, thereby further reducing computation energy consumption by up to 27.3% while maintaining satisfactory visual quality.

Original languageEnglish
Title of host publicationProceedings of the 56th Annual Design Automation Conference 2019, DAC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781450367257
DOIs
StatePublished - 2 Jun 2019
Event56th Annual Design Automation Conference, DAC 2019 - Las Vegas, United States
Duration: 2 Jun 20196 Jun 2019

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X

Conference

Conference56th Annual Design Automation Conference, DAC 2019
CountryUnited States
CityLas Vegas
Period2/06/196/06/19

Keywords

  • Energy savings
  • Graphics applications
  • Mobile devices
  • Perceptual quality
  • Similarity measurement

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  • Cite this

    Chang, Y. C., Chen, W. M., Hsiu, P. C., Lin, Y-Y., & Kuo, T. W. (2019). LSIM: Ultra lightweight similarity measurement for mobile graphics applications. In Proceedings of the 56th Annual Design Automation Conference 2019, DAC 2019 [a25] (Proceedings - Design Automation Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1145/3316781.3317856