Iterative RANSAC based adaptive birth intensity estimation in GM-PHD filter for multi-target tracking
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- 作者：Jingjing Wua ; b ; wjjlady720@jiangnan.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Ke Lia ; b ; Qiuju Zhanga ; b ; Wei Ana ; b ; Yi Jianga ; b ; Xueliang Pinga ; b ; Peng Chenc
- 关键词：PHD filter ; Multi-target tracking ; Gaussian mixture ; Adaptive birth intensity ; RANSAC
- 刊名：Signal Processing
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：131
- 期：Complete
- 页码：412-421
- 全文大小：3360 K
文摘
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A multi-target tracking algorithm combining PHD filter with adaptive detection of newborn targets is developed.
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A novel birth intensity estimation approach is proposed to accurately and robustly determine the intensity of new targets.
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A measurement classifying approach is proposed to remove errors from the measurement uncertainties.
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A spatio-temporal filtering based on I-RANSAC is proposed to further eliminate errors of birth intensity from clutter.
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The proposed tracker can improve number and state estimation of targets in complicated scenarios.