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Efficient hardware architecture for Particle Filter based object tracking

机译:用于基于粒子过滤器的对象跟踪的高效硬件架构

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In this paper, an efficient hardware architecture of Sample Important Resample Particle Filter (SIRF) is presented. This architecture carries out the sampling, weighting, and output calculations steps concurrently. The resampling step is implemented in a massively parallel form. For weight computation step, piecewise linear function is used instead of the classical exponential function. This decreases the complexity of the architecture without degrading the results. The presented architecture allows efficient memory utilization in addition to resource saving. Synthesis results confirmed the resource reduction and speed up advantages of our design. The hardware implementation targeted an Enhanced PF for object tracking application. FPGA is used as the implementation hardware platform.
机译:本文提出了一种有效的重要样本重采样粒子滤波器(SIRF)硬件架构。该体系结构同时执行采样,加权和输出计算步骤。重采样步骤以大规模并行的形式实现。对于权重计算步骤,使用分段线性函数代替经典指数函数。这降低了体系结构的复杂性而不会降低结果。所展示的架构除了节省资源外,还可以有效利用内存。综合结果证实了资源的减少并加快了我们设计的优势。硬件实现的目标是针对对象跟踪应用程序的增强型PF。 FPGA被用作实现硬件平台。

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