论文标题
实时和节能的暹罗跟踪 - 一种硬件软件方法
Towards real-time and energy efficient Siamese tracking -- a hardware-software approach
论文作者
论文摘要
在过去的几年中，暹罗跟踪器一直是每个视觉对象跟踪（fot）挑战的最新解决方案之一。但是，精确的计算复杂性非常出色：要实现实时处理，这些跟踪器必须大规模平行，并且通常在高端GPU上运行。易于实施，这种方法是能量消耗的，因此不能在许多低功率应用中使用。为了克服这一点，可以使用节能嵌入式设备，例如与可编程逻辑（FPGA）连接ARM处理器系统的异质平台。在这项工作中，我们提出了众所周知的完全连接的暹罗跟踪器（SIAMFC）的硬件软件实现。我们使用算法 - 加速器共同设计开发了一个用于Finn加速器的量化网络，并执行了设计空间探索，以实现最佳的效率与能量比（由FPS和使用的资源确定）。对于我们的网络，在Zynq Ultrascale+ MPSOC ZCU104的可编程逻辑部分运行，我们以跟踪器准确度与其浮点对应器以及原始的SiAMFC网络一起实现了将近50帧的每秒框架。通过在FPGA上加速网络的网络实现的完整跟踪系统可达到17 fps。这些结果使我们能够弥合高度准确但能源的算法与准备在低功率边缘系统中使用的节能解决方案之间的差距。
Siamese trackers have been among the state-of-the-art solutions in each Visual Object Tracking (VOT) challenge over the past few years. However, with great accuracy comes great computational complexity: to achieve real-time processing, these trackers have to be massively parallelised and are usually run on high-end GPUs. Easy to implement, this approach is energy consuming, and thus cannot be used in many low-power applications. To overcome this, one can use energy-efficient embedded devices, such as heterogeneous platforms joining the ARM processor system with programmable logic (FPGA). In this work, we propose a hardware-software implementation of the well-known fully connected Siamese tracker (SiamFC). We have developed a quantised Siamese network for the FINN accelerator, using algorithm-accelerator co-design, and performed design space exploration to achieve the best efficiency-to-energy ratio (determined by FPS and used resources). For our network, running in the programmable logic part of the Zynq UltraScale+ MPSoC ZCU104, we achieved the processing of almost 50 frames-per-second with tracker accuracy on par with its floating point counterpart, as well as the original SiamFC network. The complete tracking system, implemented in ARM with the network accelerated on FPGA, achieves up to 17 fps. These results bring us towards bridging the gap between the highly accurate but energy-demanding algorithms and energy-efficient solutions ready to be used in low-power, edge systems.
