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Model Update Particle Filter for Multiple Objects Detection and Tracking

Yunji Zhao, Hailong Pei

International Journal of Computational Intelligence Systems · 2012

doi:10.1080/18756891.2012.733235 (opens in a new tab)

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Abstract

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 also use color histogram(CH) and histogram of orientated gradients(HOG) to represent the objects, model update is realized by 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 results. Experiments on video sequences demonstrate that the method presented in this paper can realize multiple objects detection and tracking.

Abstract licence: CC BY-NC-ND

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