3D Multi Person Tracking With Dual 360° Cameras
3D Multi Person Tracking With Dual 360° Cameras
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DOI：
10.1109/icip40778.2020.9191269
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发表时间：
2020-05
期刊：
影响因子：
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通讯作者：
Matthew Shere;Hansung Kim;A. Hilton
中科院分区：
文献类型：
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作者：
Matthew Shere;Hansung Kim;A. Hilton
人的跟踪是计算机视觉中经常研究的一个方面，在安全、自动驾驶和娱乐方面都有应用。然而，尽管它们提供了优势，由于投影失真，目前很少有解决方案适用于360°摄像机。本文提出了一种简单而稳健的方法，用于从一对360°摄像机中对场景中的多人进行3D跟踪。通过使用2D姿态信息，而不是潜在的不可靠的3D位置或重复的颜色信息，我们创建了一个跟踪器，既外观独立，又能够在窄基线下操作。我们的结果展示了360°场景的最先进性能，以及处理垂直轴旋转的能力。
Person tracking is an often studied facet of computer vision, with applications in security, automated driving and entertainment. However, despite the advantages they offer, few current solutions work for 360° cameras, due to projection distortion. This paper presents a simple yet robust method for 3D tracking of multiple people in a scene from a pair of 360° cameras. By using 2D pose information, rather than potentially unreliable 3D position or repeated colour information, we create a tracker that is both appearance independent as well as capable of operating at narrow baseline. Our results demonstrate state of the art performance on 360° scenes, as well as the capability to handle vertical axis rotation.