Multiple Human Tracking Using Particle Filter with Gaussian Process Dynamical Model
<p>Abstract</p> <p>We present a particle filter-based multitarget tracking method incorporating Gaussian process dynamical model (GPDM) to improve robustness in multitarget tracking. With the particle filter Gaussian process dynamical model (PFGPDM), a high-dimensional target traje...
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2008-01-01
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Series: | EURASIP Journal on Image and Video Processing |
Online Access: | http://jivp.eurasipjournals.com/content/2008/969456 |
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doaj-6557cbe15d294a06bc46efc8d4bbac632020-11-25T00:36:52ZengSpringerOpenEURASIP Journal on Image and Video Processing1687-51761687-52812008-01-0120081969456Multiple Human Tracking Using Particle Filter with Gaussian Process Dynamical ModelWang JingYin YafengMan Hong<p>Abstract</p> <p>We present a particle filter-based multitarget tracking method incorporating Gaussian process dynamical model (GPDM) to improve robustness in multitarget tracking. With the particle filter Gaussian process dynamical model (PFGPDM), a high-dimensional target trajectory dataset of the observation space is projected to a low-dimensional latent space in a nonlinear probabilistic manner, which will then be used to classify object trajectories, predict the next motion state, and provide Gaussian process dynamical samples for the particle filter. In addition, Histogram-Bhattacharyya, GMM Kullback-Leibler, and the rotation invariant appearance models are employed, respectively, and compared in the particle filter as complimentary features to coordinate data used in GPDM. The simulation results demonstrate that the approach can track more than four targets with reasonable runtime overhead and performance. In addition, it can successfully deal with occasional missing frames and temporary occlusion.</p>http://jivp.eurasipjournals.com/content/2008/969456 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Wang Jing Yin Yafeng Man Hong |
spellingShingle |
Wang Jing Yin Yafeng Man Hong Multiple Human Tracking Using Particle Filter with Gaussian Process Dynamical Model EURASIP Journal on Image and Video Processing |
author_facet |
Wang Jing Yin Yafeng Man Hong |
author_sort |
Wang Jing |
title |
Multiple Human Tracking Using Particle Filter with Gaussian Process Dynamical Model |
title_short |
Multiple Human Tracking Using Particle Filter with Gaussian Process Dynamical Model |
title_full |
Multiple Human Tracking Using Particle Filter with Gaussian Process Dynamical Model |
title_fullStr |
Multiple Human Tracking Using Particle Filter with Gaussian Process Dynamical Model |
title_full_unstemmed |
Multiple Human Tracking Using Particle Filter with Gaussian Process Dynamical Model |
title_sort |
multiple human tracking using particle filter with gaussian process dynamical model |
publisher |
SpringerOpen |
series |
EURASIP Journal on Image and Video Processing |
issn |
1687-5176 1687-5281 |
publishDate |
2008-01-01 |
description |
<p>Abstract</p> <p>We present a particle filter-based multitarget tracking method incorporating Gaussian process dynamical model (GPDM) to improve robustness in multitarget tracking. With the particle filter Gaussian process dynamical model (PFGPDM), a high-dimensional target trajectory dataset of the observation space is projected to a low-dimensional latent space in a nonlinear probabilistic manner, which will then be used to classify object trajectories, predict the next motion state, and provide Gaussian process dynamical samples for the particle filter. In addition, Histogram-Bhattacharyya, GMM Kullback-Leibler, and the rotation invariant appearance models are employed, respectively, and compared in the particle filter as complimentary features to coordinate data used in GPDM. The simulation results demonstrate that the approach can track more than four targets with reasonable runtime overhead and performance. In addition, it can successfully deal with occasional missing frames and temporary occlusion.</p> |
url |
http://jivp.eurasipjournals.com/content/2008/969456 |
work_keys_str_mv |
AT wangjing multiplehumantrackingusingparticlefilterwithgaussianprocessdynamicalmodel AT yinyafeng multiplehumantrackingusingparticlefilterwithgaussianprocessdynamicalmodel AT manhong multiplehumantrackingusingparticlefilterwithgaussianprocessdynamicalmodel |
_version_ |
1725303870946541568 |