Model Update Particle Filter for Multiple Objects Detection and Tracking

DOI

10.1080/18756891.2012.733235How to use a DOI?

Keywords

Color Histogram, Histogram of Oriented Gradients, Particle Filter, Gaussian Mixture Model

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.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Yunji Zhao
AU  - Hailong Pei
PY  - 2012
DA  - 2012/09/01
TI  - Model Update Particle Filter for Multiple Objects Detection and Tracking
JO  - International Journal of Computational Intelligence Systems
SP  - 964
EP  - 974
VL  - 5
IS  - 5
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2012.733235
DO  - 10.1080/18756891.2012.733235
ID  - Zhao2012
ER  -