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Video s3
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    Presenter(s)
    Zishen Wan Headshot
    Display Name
    Zishen Wan
    Affiliation
    Affiliation
    Georgia Institute of Technology
    Country
    Abstract

    In our past few years' of commercial deployment experiences, we identify localization as a critical task in autonomous machine applications, and a great acceleration target. In this paper, based on the observation that the visual frontend is a major performance and energy consumption bottleneck, we present our design and implementation of an energy-efficient hardware architecture for ORB (Oriented-Fast and Rotated-BRIEF) based localization system on FPGAs. To support our multi-sensor autonomous machine localization system, we present hardware synchronization, frame-multiplexing, and parallelization techniques, which are integrated in our design. Compared to Nvidia TX1 and Intel i7, our FPGA-based implementation achieves 5.6x and 3.4x speedup, as well as 3.0x and 34.6x power reduction, respectively.

    Slides
    • An Energy-Efficient Quad-Camera Visual System for Autonomous Machines on FPGA Platform (application/pdf)