On pedestrian detection and tracking in infrared videos
On pedestrian detection and tracking in infrared videos
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DOI：
10.1016/j.patrec.2011.12.011
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发表时间：
2012-04-15
影响因子：
5.1
通讯作者：
Yang, Jing-yu
中科院分区：
文献类型：
--
作者：
Wang, Jiang-tao;Chen, De-bao;Yang, Jing-yu
提出了一种基于红外图像的行人检测与跟踪方法。首先利用GMM背景模型将前景候选人与背景分离，然后引入形状描述器构造行人候选人的特征向量，最后根据红外图像生成的数据集或人工训练SVM分类器。在基于SVM分类器检测行人的基础上，提出了一种多线索融合算法，在粒子滤波框架下，利用边缘特征和强度特征进行行人跟踪。实验结果与各种红外视频数据库的报告，以证明我们的算法的准确性和鲁棒性。(C)2011 Elsevier B.V.保留所有权利。
This article presents an approach for pedestrian detection and tracking from infrared imagery. The GMM background model is first deployed to separate the foreground candidates from background, then a shape describer is introduced to construct the feature vector for pedestrian candidates, and a SVM classifier is trained based on datasets generated from infrared images or manually. After detecting the pedestrian based on the SVM classifier, a multi-cues fusing algorithm is provided to facilitate the task of pedestrian tracking using both edge feature and intensity feature under the particle filter framework. Experimental results with various Infrared Video Database are reported to demonstrate the accuracy and robustness of our algorithm. (C) 2011 Elsevier B.V. All rights reserved.