Smartphone Zombie Detection From LiDAR Point Cloud for Mobile Robot Safety
Smartphone Zombie Detection From LiDAR Point Cloud for Mobile Robot Safety
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DOI：
10.1109/lra.2020.2970570
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发表时间：
2020-01
影响因子：
5.2
通讯作者：
Jiaxu Wu;Y. Tamura;Yusheng Wang;Hanwool Woo;Alessandro Moro;A. Yamashita;H. Asama
中科院分区：
文献类型：
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作者：
Jiaxu Wu;Y. Tamura;Yusheng Wang;Hanwool Woo;Alessandro Moro;A. Yamashita;H. Asama
对周围环境的感知和对危险情况的预测对于自主移动机器人至关重要，尤其是在人类居住的环境中导航时。为了解决安全问题，最先进的工作集中在行人检测、跟踪和轨迹预测上。然而，只有少数研究致力于识别行人表现出的某些特定类型的危险行为。在这里，我们提出了一种跟踪增强检测方法来识别步行时使用智能手机的人，称为智能手机僵尸。用于行人检测的特征通常涉及旋转方差问题，在本文中，通过利用多目标跟踪的运动信息来解决该缺点。所提出的解决方案已通过在新收集的数据集上进行的实验得到验证。结果表明，我们的探测器可以了解智能手机僵尸的独特外观模式。因此，它可以成功地检测它们，其性能优于现有的检测方法。
Awareness of surrounding and prediction of dangerous situations is essential for autonomous mobile robots, especially during navigation in a human-populated environment. To cope with safety issues, state-of-the-art works have focused on pedestrian detection, tracking, and trajectory prediction. However, only a few studies have been conducted on recognizing some specific types of dangerous behaviors exhibited by pedestrians. Here, we propose a tracking enhanced detection method to recognize people using their smartphones while walking, referred to as smartphone zombie. Features used for pedestrian detection usually involve the rotation variance problem, and in this paper, the drawback is handled by employing motion information from multi-object tracking. The proposed solution has been validated through experiments performed on a newly collected dataset. Results showed that our detector can learn a distinct pattern of the appearance of smartphone zombies. Thus, it can successfully detect them outperforming the existed detection method.