Position reset and hybrid feature based particle filter tracking for large-size and long-term full occlusion

Position reset and hybrid feature based particle filter tracking for large-size and long-term full occlusion
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DOI:
10.1117/12.2669979
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发表时间:
2023-02
期刊:
The Visual Computer
影响因子:
--
通讯作者:
Ruijie Cao;Xina Cheng;Yanchao Liu;T. Ikenaga
Ruijie Cao;Xina Cheng;Yanchao Liu;T. Ikenaga
中科院分区:
其他
文献类型:
--
作者:
Ruijie Cao;Xina Cheng;Yanchao Liu;T. Ikenaga

文献摘要

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目标跟踪是计算机视觉领域的一个重要研究方向,在视频监控、车辆导航等领域有着广泛的应用。但遮挡问题是应用中最具挑战性的问题之一。虽然在目标跟踪领域有很多方法都是针对遮挡场景的,但是对于遮挡范围大、遮挡时间长的遮挡问题仍然无法解决。针对这一问题,提出了一种基于粒子滤波的大尺寸遮挡物长时间完全遮挡情况下的可靠跟踪方法。在本文中,大尺寸被定义为在固定分辨率图像中像素宽度从350到600。长期定义为遮挡帧数从180到600。首先,本文提出了一个粒子位置重置模块来代替遮挡期间的重置过程,以解决遮挡后目标丢失的问题。此外,提出了一种基于混合特征的似然模型,用于遮挡发生和结束的判断。极端遮挡情况序列上的实验表明,这些具有挑战性的场景所提出的工作的可靠性和准确性。该算法最终在测试序列上实现了平均92%的成功率。
Object tracking plays an important role in the computer vision field and has many applications such as video surveillance and vehicle navigation. But the occlusion problem is one of the most challenging problems in the applications. Although there are many approaches in the object tracking field that focus on dealing with occlusion scenes, the occlusion with large size barriers and long occlusion time still cannot be solved. To handle the problems, this paper proposes a reliable tracking method based on particle filter focus on long-term full occlusion with large size barriers. In this paper the large size is defined as pixel width from 350 to 600 in fixed resolution images. and the long term is defined as occlusion frame number from 180 to 600. First, this paper proposed a particle position reset module to replace the resampling process during the occlusion periods to solve the problem of losing the target after occlusion. In addition, a hybrid feature based likelihood model is proposed for the occlusion happening and ending judgments. Experiments on the extreme occlusion situation sequences demonstrate the reliability and accuracy of the proposed work on these challenging scenes. The algorithm finally implements the average 92% success rate at the tested sequences.