Embedded Frame Compression for Energy-Efficient Computer Vision Systems

Li Guo, Dajiang Zhou, Jinjia Zhou, Shinji Kimura

研究成果: Conference contribution

1 引用 (Scopus)

抜粋

Computer vision applications are rapidly gaining popularity in embedded systems, which typically involve a difficult trade-off between vision performance and energy consumption under a constraint of real-time processing throughput. Recently, hardware (FPGA and ASIC-based) implementations have emerged that significantly improve the energy efficiency of vision computation. These implementations, however, often involve intensive memory traffic that retains a significant portion of energy consumption at the system level. To address this issue, we present a lossy embedded compression framework to exploit the trade-off between vision performance and memory traffic for input images. Differential pulse-code modulation-based gradient-oriented quantization is developed as the lossy compression algorithm. We also present its hardware design that supports up to 12-scale 1080p@60fps real-time processing. For histogram of oriented gradient-based deformable part models on VOC2007, the proposed framework achieved a 49.6%-60.5% memory traffic reduction at a detection rate degradation of 0.05%-0.34%. For AlexNet on ImageNet, memory traffic reduction achieved up to 60.8% with less than 0.61% classification rate degradation.

元の言語English
ホスト出版物のタイトル2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings
出版者Institute of Electrical and Electronics Engineers Inc.
2018-May
ISBN(電子版)9781538648810
DOI
出版物ステータスPublished - 2018 4 26
イベント2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Florence, Italy
継続期間: 2018 5 272018 5 30

Other

Other2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018
Italy
Florence
期間18/5/2718/5/30

    フィンガープリント

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

これを引用

Guo, L., Zhou, D., Zhou, J., & Kimura, S. (2018). Embedded Frame Compression for Energy-Efficient Computer Vision Systems. : 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings (巻 2018-May). [8351483] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCAS.2018.8351483