On-chip pulse based parallel neural circuits for object-tracking system

A scheme of pulse based neural circuits for object tracking is proposed. Different from the conventional frame-based methodology, the proposed design utilises parallel arrays of circuits to extract pixels with significant temporal contrast, which are indicators of moving objects. It can be implemented on an FPGA chip in full parallelism and improves the tracking performance dramatically. Moreover, its integrate-and-fire neural model can cluster concave data sets. Experimental results show that the proposed scheme outperforms conventional methods.