S. Liu, Alexandros Papakonstantinou, Hongjun Wang, Deming Chen
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引用次数: 46
摘要
目标跟踪是计算机视觉应用中的一项重要任务。其中一个关键的挑战是实时速度要求。本文采用高效的并行架构,在可重构硬件上实现了一个目标跟踪系统。在我们的实现中,我们采用了基于背景减法的算法。所设计的目标跟踪器利用硬件并行性来实现高系统速度。我们还提出了一种双目标区域搜索技术,以进一步提高系统在复杂跟踪条件下的性能。对于硬件实现,我们使用altera Stratix III EP3SL340H1152C2 FPGA器件。我们将提出的基于fpga的实现与运行在2.2 GHz处理器上的软件实现进行了比较。对于复杂的视频输入,观察到的加速可以达到100倍以上。
Object tracking is an important task in computer vision applications. One of the crucial challenges is the real-time speed requirement. In this paper we implement an object tracking system in reconfigurable hardware using an efficient parallel architecture. In our implementation, we adopt a background subtraction based algorithm. The designed object tracker exploits hardware parallelism to achieve high system speed. We also propose a dual object region search technique to further boost the performance of our system under complex tracking conditions. For our hardware implementation we use the Alter a Stratix III EP3SL340H1152C2 FPGA device. We compare the proposed FPGA-based implementation with the software implementation running on a 2.2 GHz processor. The observed speedup can reach more than 100X for complex video inputs.