@inproceedings{eacdf9c0515d4361a5fb80d1757a888d,
title = "Real-time target tracking system for person-following robot",
abstract = "In this paper, we propose a very fast and robust tracking system for the person-following robot. Our robot tracking system could detect human automatically in the field of view. The user issues a command by hand gesture as a flag of start, then the person-following robot locks the user as the target and starts tracking. Our robot system consists of two parts: a basic tracker which uses the skeletal tracking algorithm that is provided by Kinect SDK and an auxiliary tracker which utilizes Camshift algorithm. When the basic tracker fails, the auxiliary tracker utilizes Camshift ro correct the wrong result to ensure the robot obtains the right location. After getting the location of the target, we predict the position of next moment by the Extended Kalman filter. The proposed system is verified under three real environments: linear tracking, curvilinear tracking and tracking in a narrow space. The experimental results demonstrate that our robot system can robustly follow a person.",
keywords = "Camshift, Extended Kalman filter, Person-following robot, Skeletal tracking",
author = "Qimin Ren and Qingjie Zhao and Hui Qi and Lingrui Li",
note = "Publisher Copyright: {\textcopyright} 2016 TCCT.; 35th Chinese Control Conference, CCC 2016 ; Conference date: 27-07-2016 Through 29-07-2016",
year = "2016",
month = aug,
day = "26",
doi = "10.1109/ChiCC.2016.7554324",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "6160--6165",
editor = "Jie Chen and Qianchuan Zhao and Jie Chen",
booktitle = "Proceedings of the 35th Chinese Control Conference, CCC 2016",
address = "United States",
}