Model Update Particle Filter for Multiple Objects Detection and Tracking

摘要

Multiple objects tracking is a challenging task. This article presents an algorithm which can detect and track multiple objects, and update target model automatically. The contributions of this paper as follow: Firstly, we use color histogram(HC) and histogram of orientated gradients(HOG) to represent the objects, model update is realized under the frame of kalman filter and gaussian model, secondly we use Gaussian Mixture Model(GMM) and Bhattacharyya distance to detect object appearance. Particle filter with combined features and model update mechanism can improve tracking effects. Experiments on video sequences demonstrate that multiple objects tracking based on improved algorithm have good performance.