High-speed tracking system based on Multi-parallel-core processor and CNN algorithm

Abstract

This paper proposes a high-speed tracking system based on a multi-parallel-core processor architecture and a convolution neural network (CNN)-based tracking algorithm. Multiple processing cores are designed in the processor architecture, and they can parallel carry out operations. Each processing core can access data from another processing core through a interconnect control module (ICM), which make it easy to run CNN. Other components, such as Microprocessor Unit (MPU) and Data Transfer Control Module (DTCM), are also designed for global controlling and data transmitting. The proposed tracking algorithm is based on CNN which mainly contains three convolution (CONV) layers and one full connection (FC) layer. Based on an analysis of equivalence, the softmax layer is discarded when inferring. Because the conciseness and the effectiveness, the algorithm can be executed efficiently on the processor architecture, and Experiment results demonstrate that the tracking system based on the proposed algorithm and processor can achieve high-speed target tracking up to 880 fps.