The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Mengesan situasi kecemasan adalah sangat penting kepada sistem pengawasan untuk orang seperti warga tua yang tinggal bersendirian. Sistem tindak balas kecemasan berasaskan penglihatan dengan robot mudah alih paramedik dibentangkan dalam kertas ini. Sistem yang dicadangkan terdiri daripada sistem pengesanan kecemasan berasaskan penglihatan dan robot mudah alih sebagai paramedik. Sistem pengesanan kecemasan berasaskan penglihatan mengesan kecemasan dengan menjejaki orang dan mengesan tindakan mereka daripada jujukan imej yang diperoleh oleh kamera pengawasan tunggal. Untuk mengenali tindakan manusia, kawasan minat dibahagikan dari latar belakang menggunakan kaedah pengekstrakan gumpalan dan dijejaki secara berterusan menggunakan model generik. Kemudian MHI (Imej Sejarah Pergerakan) untuk orang yang dijejaki dibina oleh maklumat siluet gumpalan rantau dan tindakan model. Keadaan kecemasan akhirnya dikesan dengan menggunakan maklumat ini pada rangkaian saraf. Apabila kecemasan dikesan, robot mudah alih boleh membantu untuk mendiagnosis status orang dalam situasi tersebut. Untuk menghantar robot mudah alih ke kedudukan yang sepatutnya, kami melaksanakan algoritma navigasi robot mudah alih berdasarkan jarak antara orang dan robot mudah alih. Kami mengesahkan sistem kami dengan menunjukkan kadar pengesanan kecemasan dan demonstrasi tindak balas kecemasan menggunakan robot mudah alih.
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Salinan
Il-Woong JEONG, Jin CHOI, Kyusung CHO, Yong-Ho SEO, Hyun Seung YANG, "A Vision-Based Emergency Response System with a Paramedic Mobile Robot" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 7, pp. 1745-1753, July 2010, doi: 10.1587/transinf.E93.D.1745.
Abstract: Detecting emergency situation is very important to a surveillance system for people like elderly live alone. A vision-based emergency response system with a paramedic mobile robot is presented in this paper. The proposed system is consisted of a vision-based emergency detection system and a mobile robot as a paramedic. A vision-based emergency detection system detects emergency by tracking people and detecting their actions from image sequences acquired by single surveillance camera. In order to recognize human actions, interest regions are segmented from the background using blob extraction method and tracked continuously using generic model. Then a MHI (Motion History Image) for a tracked person is constructed by silhouette information of region blobs and model actions. Emergency situation is finally detected by applying these information to neural network. When an emergency is detected, a mobile robot can help to diagnose the status of the person in the situation. To send the mobile robot to the proper position, we implement mobile robot navigation algorithm based on the distance between the person and a mobile robot. We validate our system by showing emergency detection rate and emergency response demonstration using the mobile robot.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.1745/_p
Salinan
@ARTICLE{e93-d_7_1745,
author={Il-Woong JEONG, Jin CHOI, Kyusung CHO, Yong-Ho SEO, Hyun Seung YANG, },
journal={IEICE TRANSACTIONS on Information},
title={A Vision-Based Emergency Response System with a Paramedic Mobile Robot},
year={2010},
volume={E93-D},
number={7},
pages={1745-1753},
abstract={Detecting emergency situation is very important to a surveillance system for people like elderly live alone. A vision-based emergency response system with a paramedic mobile robot is presented in this paper. The proposed system is consisted of a vision-based emergency detection system and a mobile robot as a paramedic. A vision-based emergency detection system detects emergency by tracking people and detecting their actions from image sequences acquired by single surveillance camera. In order to recognize human actions, interest regions are segmented from the background using blob extraction method and tracked continuously using generic model. Then a MHI (Motion History Image) for a tracked person is constructed by silhouette information of region blobs and model actions. Emergency situation is finally detected by applying these information to neural network. When an emergency is detected, a mobile robot can help to diagnose the status of the person in the situation. To send the mobile robot to the proper position, we implement mobile robot navigation algorithm based on the distance between the person and a mobile robot. We validate our system by showing emergency detection rate and emergency response demonstration using the mobile robot.},
keywords={},
doi={10.1587/transinf.E93.D.1745},
ISSN={1745-1361},
month={July},}
Salinan
TY - JOUR
TI - A Vision-Based Emergency Response System with a Paramedic Mobile Robot
T2 - IEICE TRANSACTIONS on Information
SP - 1745
EP - 1753
AU - Il-Woong JEONG
AU - Jin CHOI
AU - Kyusung CHO
AU - Yong-Ho SEO
AU - Hyun Seung YANG
PY - 2010
DO - 10.1587/transinf.E93.D.1745
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2010
AB - Detecting emergency situation is very important to a surveillance system for people like elderly live alone. A vision-based emergency response system with a paramedic mobile robot is presented in this paper. The proposed system is consisted of a vision-based emergency detection system and a mobile robot as a paramedic. A vision-based emergency detection system detects emergency by tracking people and detecting their actions from image sequences acquired by single surveillance camera. In order to recognize human actions, interest regions are segmented from the background using blob extraction method and tracked continuously using generic model. Then a MHI (Motion History Image) for a tracked person is constructed by silhouette information of region blobs and model actions. Emergency situation is finally detected by applying these information to neural network. When an emergency is detected, a mobile robot can help to diagnose the status of the person in the situation. To send the mobile robot to the proper position, we implement mobile robot navigation algorithm based on the distance between the person and a mobile robot. We validate our system by showing emergency detection rate and emergency response demonstration using the mobile robot.
ER -