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People re-identification across non-overlapping cameras using group features

机译：使用群组功能跨非重叠摄像机重新识别人员

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摘要

This paper proposes methods for people re-identification across non-overlapping cameras. We improve the robustness of re-identification by using additional group features acquired from the groups of people detected by each camera. People are grouped by discriminatively classifying the spatio-temporal features of their trajectories into those of grouped people and non-grouped people. Thereafter, three group features are obtained in each group and utilized with other general features of each person (e.g., color histogram, transit time between cameras, etc.) for people re-identification. Our experimental results have demonstrated improvements in people grouping and people re-identification when our proposed methods have been applied to a public dataset.
机译：本文提出了在不重叠的摄像机之间进行人员重新识别的方法。通过使用从每个摄像机检测到的人群中获取的其他人群特征，我们提高了重新识别的鲁棒性。通过将轨迹的时空特征进行区分，将人归类为成群人和非成群人。此后，在每个组中获得三个组特征，并将其与每个人的其他一般特征（例如，颜色直方图，相机之间的通过时间等）一起用于人们的重新识别。我们的实验结果表明，当将我们提出的方法应用于公共数据集时，人员分组和人员重新识别得到了改善。

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