An object tracking method using deep learning and adaptive particle filter for night fusion image

Abstract

In this paper, we propose an online visual tracking algorithm for fused sequences via deep learning and adaptive Particle filter (PF). Our algorithm pretrains a simplified Convolution Neural Network (CNN) to obtain a generic target representation. The outputs from the hidden layers of the network help to form the tracking model for an online PF. During tracking, the moving information guides the distribution of particle samples. The tests illustrate competitive performance compared to the state-of-art tracking algorithms especially when the target or camera moves quickly.