Pedestrian Tracking in Infrared Video Based on Improved Particle Filter

Abstract:

An improved particle filter method for pedestrian tracking in infrared video is proposed. The objects are described in the scheme of particle filter using Histogram of Oriented Gradients(HOG). Instead of the Euclidean distance in color space, the HOG is employed to describe the similarity and compute the weights of the samples, which solves the issue of lack of color information for infrared video. Experimental results show that the method is more accurate and effective tracking of moving targets in complex scenes than traditional particle filter algorithm in infrared video.