Target tracking method and system of spiking neural network based on event camera

A target tracking system of a spiking neural network based on an event camera, comprising a data stream acquiring module, a high time resolution event frame generating module, a network training module, and a network output module;

• wherein the data stream acquiring module is configured for acquiring a data stream of asynchronous events in a high dynamic scene of a target by an event camera as input data;
• the high time resolution event frame generating module is configured for dividing the data stream of the asynchronous events into synchronous event frames with millisecond time resolution by asynchronous event accumulation, wherein the synchronous event frames are binary images similar to a spiking;
• the network training module is configured for training a twin network based on a spiking neural network by a gradient substitution algorithm with a target image as a template image denoted as z and a complete image as a searched image denoted as x, wherein the twin network comprises a feature extractor with weight sharing and a cross-correlation calculator for calculating a position of the target, the target image is an image of the target in the synchronous event frames, and the complete image comprises any one of all the synchronous event frames;
• and
• the network output module is configured for tracking the target by a trained twin network with interpolating a result of feature mapping to up-sample and obtaining the position of the target in an original image.