Content-Adaptive Memory for Viewer-Aware Energy-Quality Scalable Mobile Video Systems

Edstrom, Jonathon; Gong, Yifu; Haidous, Ali; Humphrey, Brittney; McCourt, Mark E.; Xu, Yihuan; Wang, Jinhui; Gong, Na

doi:10.1109/access.2019.2908997

Cited by 8 publications

(35 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[4][5][6] Ref. [7] General design techniques in order to accommodate the large amount of video data. However, these design techniques usually come with significant implementation overhead (e.g., silicon area, delay) to solve failure problems in memories.…”

Section: Different Surroundingsmentioning

confidence: 99%

“…However, these design techniques usually come with significant implementation overhead (e.g., silicon area, delay) to solve failure problems in memories. We have recently explored viewer-aware video memory design by investigating the impact of illuminance levels in different viewing surroundings on the viewer's experience [4,5,6,7], as shown in Fig. 1.…”

Section: Different Surroundingsmentioning

confidence: 99%

“…A vast amount of research has been conducted to improve the power efficiency of video data storage. State-of-the-art, power-efficient video memories consist of either approximate memory with application-level information [8,9,10,11,12] or viewer-aware memories with an awareness of viewer's experience [4,5,6,7]. In this section, some of the existing work related to the proposed technique are briefly reviewed, and the detailed comparison analysis will be provided in Section VII.…”

Section: State Of the Artmentioning

confidence: 99%

“…We have investigated viewer-aware low-power video memory techniques in [4,5,6]: where an increased amount of ambient luminance allows for a larger number of bits to be truncated without noticeable degradation to the viewers. Very recently, we studied the impact of video content characteristics on viewer's experience to enable video content-adaptive memory with dynamic energy-quality tradeoff [7]. However, the technique determined the number of truncated LSBs based on the averaged plain macroblock percentage of an entire video sample; therefore, it was only effective to store low-motion videos with a stationary camera or containing a reporter in a video cast use-case.…”

Section: B Viewer-aware Video Memorymentioning

confidence: 99%

“…2 shows one example. The output quality of the video (Video tag: wF6lvdXXwc4 [14]) using the technique in [7] is shown in Fig. 2 (a).…”

Section: A Motivational Examplementioning

confidence: 99%

See 4 more Smart Citations

Content-Adaptable ROI-Aware Video Storage for Power-Quality Scalable Mobile Streaming

et al. 2022

Self Cite

View full text Add to dashboard Cite

The demand for mobile video streams is constantly increasing. With this demand comes a need for mobile devices to receive more videos at ever increasing quality. However, due to the large size of video data and intensive computational requirements, video streaming requires frequent memory access that consume a substantial amount of mobile device power; as a result, the battery life of mobile devices is limited. In this paper, we present a video content-adaptable Region-of-Interest (ROI)-aware video storage technique that promotes power savings. During the video encoding process on the transmitting server, based on the macroblock variance and ROI characterization, the "macroblocks of interest" are identified and embedded in the encoded bitstream. In the decoding process, a new frame buffer with dynamic power-quality trade-off is presented to adapt to the macroblock characteristics during run-time. Results from the system-level and circuit-level simulations show that the proposed technique enables substantially more truncated bits and significant power savings while delivering similar or better video quality as compared to other state-of-theart solutions.

show abstract

Section: Different Surroundingsmentioning

confidence: 99%

Section: Different Surroundingsmentioning

confidence: 99%

Section: State Of the Artmentioning

confidence: 99%

Section: B Viewer-aware Video Memorymentioning

confidence: 99%

“…2 shows one example. The output quality of the video (Video tag: wF6lvdXXwc4 [14]) using the technique in [7] is shown in Fig. 2 (a).…”

Section: A Motivational Examplementioning

confidence: 99%

See 3 more Smart Citations

Content-Adaptable ROI-Aware Video Storage for Power-Quality Scalable Mobile Streaming

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

Approximate Memory for Low-Power Video Applications

et al. 2023

Self Cite

View full text Add to dashboard Cite

In this paper, an error-correction code (ECC)-enabled memory design with selective bit hardening is proposed for approximate data storage. Approximate memory is suitable for errortolerant applications, and can achieve low-power design goals within targeted quality. Our design offers approximately 90% power savings compared to traditional memory, without compromising perceived quality. To the best of our knowledge, combining selective bit hardening with ECC is a novel approach to ensure the protection of MSBs and protect other faulty bits, respectively. Our proposed method requires no area overhead for MSB hardening, other than one additional input pin; and area overhead for implementing ECC is minimal.INDEX TERMS Approximate memory, videos, error-correction code (ECC), memory, power consumption, video quality, power-quality trade-off, and bit hardening.

show abstract

A Low Power Two Lenses Wireless Panoramic Micro-Endoscopy Implemented Using Voltage-Current Adjuster and 3D-PCB Stacking Technology

Yang

Hsu

Cheng

et al. 2022

2022 IEEE Biomedical Circuits and Systems Conference (BioCAS)

View full text Add to dashboard Cite

Content-Adaptive Memory for Viewer-Aware Energy-Quality Scalable Mobile Video Systems

Cited by 8 publications

References 26 publications

Content-Adaptable ROI-Aware Video Storage for Power-Quality Scalable Mobile Streaming

Content-Adaptable ROI-Aware Video Storage for Power-Quality Scalable Mobile Streaming

Approximate Memory for Low-Power Video Applications

A Low Power Two Lenses Wireless Panoramic Micro-Endoscopy Implemented Using Voltage-Current Adjuster and 3D-PCB Stacking Technology

Contact Info

Product

Resources

About