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HcveAcc: A High-Performance and Energy-Efficient Accelerator for Tracking Task in VSLAM System

机译:HcveAcc:一种用于VSLAM系统中跟踪任务的高性能,节能加速器

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Visual SLAM (vSLAM) is a critical computer vision technology that is able to build a map of an unknown environment and perform location, simultaneously leveraging the partially built map. While existing several software SLAM processing frameworks, underlying general-purpose processors still hardly achieve the real-time SLAM at a reasonably low cost. In this paper, we propose HcveAcc, the first specialized CMOS-based hardware accelerator to help optimize the tracking task in the vSLAM system with high-performance and energy-efficient. Our HcveAcc targets to solve the time overhead bottleneck in the tracking process—high-density feature extraction and high-precision descriptor generation, and provides a configurable hardware architecture that handles higher resolution image data. We have implemented the HcveAcc in a 28nm CMOS technology using commercial EDA tools and evaluated it for the EuRoC and TUM dataset to demonstrate the robustness and accuracy in the SLAM tracking procedure. Our results show that HcveAcc achieves 4.3X speedup while consuming much less energy compared with state-of-the-art FPGA solutions.
机译:Visual SLAM(vSLAM)是一项关键的计算机视觉技术,能够构建未知环境的地图并执行定位,同时利用部分构建的地图。尽管现有几种软件SLAM处理框架,但底层通用处理器仍很难以合理的低成本实现实时SLAM。在本文中,我们提出了HcveAcc,这是第一个基于CMOS的专门硬件加速器,以帮助在vSLAM系统中以高性能和节能方式优化跟踪任务。我们的HcveAcc旨在解决跟踪过程中的时间开销瓶颈(高密度特征提取和高精度描述符生成),并提供可配置的硬件体系结构,以处理高分辨率图像数据。我们已经使用商用EDA工具在28nm CMOS技术中实现了HcveAcc,并针对EuRoC和TUM数据集对其进行了评估,以证明SLAM跟踪过程的鲁棒性和准确性。我们的结果表明,与最新的FPGA解决方案相比,HcveAcc的速度提高了4.3倍,而能耗却大大降低。

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