Improved personal identification method for guide robots using dress color information via KINECT

Seiji Sugiyama, T. Wada
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Abstract

In this paper, a Simple Personal Identification (SPI) method using Dress Color Information (DCI) for guide robots is proposed. The DCI is a small number of color information that is only calculated at narrow areas around a user's (guided person's) joint positions obtained via KINECT on a mobile robot. The SPI method includes not only the person's skeletal information but also the DCI. This method can identify the specific user in real time. As a result, even if the mobile robot loses the user temporarily when there are many people present, it can find the user properly and promptly. Our previous research had four problems as follows: 1) there is a position error between skeletal joint positions and pixel positions in RGBA camera image, 2) the narrow areas around joint positions often overflows from the dress areas, 3) changing lighting environments causes wrong results, and 4) the personal conformity is unstable. To cope with these difficulties, an improved calculating method using correction functions and color information of all joint points as a vector different from previous method is proposed in this research. The experimental results show the accuracy of our new method.
基于KINECT的引导机器人服装颜色信息识别方法的改进
提出了一种基于服装颜色信息(DCI)的引导机器人简单身份识别(SPI)方法。DCI是通过移动机器人上的KINECT获得的,仅在用户(被引导者)关节位置周围的狭窄区域计算的少量颜色信息。SPI方法不仅包括人的骨骼信息,还包括DCI。该方法可以实时识别特定用户。因此,即使在人多的情况下,移动机器人暂时失去了用户,它也能正确、及时地找到用户。我们之前的研究存在以下四个问题:1)骨骼关节位置与RGBA相机图像中的像素位置存在位置误差,2)关节位置周围的狭窄区域经常从服装区域溢出,3)光照环境的变化导致结果错误,4)个人一致性不稳定。针对这些困难,本研究提出了一种不同于以往的计算方法,采用校正函数和所有连接点的颜色信息作为矢量进行计算。实验结果表明了新方法的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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