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Person Identification Using Top-View Image with Depth Information

机译:使用具有深度信息的顶视图图像进行人员识别

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摘要

In this paper, the authors describe a novel image-based person identification task. Traditional face-based person identification methods have a low tolerance for occluded situation, such as overlapping of people in an image. The authors focus on an image from an overhead camera. The authors utilize depth information for the identification task By using depth information, the authors can capture the precise person's area and rich information for the identification task as compared with popular RGB cameras. The authors apply four features extracted from images based on depth information to the identification method; (1) estimated body height, (2) estimated body dimensions, (3) estimated body size and (4) depth histogram. In the experiment, the authors evaluated two situations; (a) standing in front of a door and (b) touching a doorknob. The identification accuracy rates are 94.4% and 91.4% on the two situations. The authors obtained the high accuracy by the proposed method.
机译:在本文中,作者描述了一种新颖的基于图像的人识别任务。传统的基于面部的人识别方法对遮挡情况(例如图像中人的重叠)的容忍度较低。作者专注于高架摄像机的图像。作者将深度信息用于识别任务通过使用深度信息,与流行的RGB相机相比,作者可以捕获准确的人的区域和丰富的信息来进行识别任务。作者将基于深度信息从图像中提取的四个特征应用于识别方法。 (1)估计身高,(2)估计身高,(3)估计身高和(4)深度直方图。在实验中,作者评估了两种情况。 (a)站在门前和(b)触摸门把手。两种情况下的识别准确率分别为94.4%和91.4%。作者通过提出的方法获得了很高的精度。

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