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首页> 外文会议>2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems >Occlusion handling and track management method of high-level sensor fusion for robust pedestrian tracking
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Occlusion handling and track management method of high-level sensor fusion for robust pedestrian tracking

机译：鲁棒行人跟踪的高级传感器融合的遮挡处理和轨道管理方法

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摘要

In object tracking field, occlusion situations between objects are important factors that degrade the performance of tracking algorithms. In this paper, we present a track management method in the tracking level to solve the discontinuous tracking problem caused by occlusions between detected objects. This work is performed by predicting the occlusion situation between detected objects and managing the state of tracks based on an approach to track-to-track fusion in a high-level sensor fusion approach using a lidar and a monocular camera sensor. The occlusion prediction is computed by taking into account the width, length, position and azimuth angle of the detected objects. The track management system manages the occlusion state of the track from the result of occlusion prediction as well as the initialization, creation, confirmation and deletion of the tracks. The proposed approach has been verified in the occlusion situation between pedestrians, and our experimental results showed the intended performance in the occlusion situation between pedestrians.
机译：在对象跟踪领域，对象之间的遮挡情况是降低跟踪算法性能的重要因素。在本文中，我们提出了一种跟踪级别的跟踪管理方法，以解决由检测对象之间的遮挡引起的不连续跟踪问题。通过预测使用激光雷达和单眼相机传感器的高级传感器融合方法中的轨道到轨道融合方法，可以预测检测到的对象之间的遮挡情况并管理轨道状态，从而完成这项工作。通过考虑检测到的物体的宽度，长度，位置和方位角来计算遮挡预测。轨道管理系统根据闭塞预测结果以及轨道的初始化，创建，确认和删除来管理轨道的闭塞状态。该方法已经在行人之间的遮挡情况下得到了验证，我们的实验结果显示了在行人之间的遮挡情况下的预期性能。

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