Development of Robust Behaviour Recognition for an at-Home Biomonitoring Robot with Assistance of Subject Localization and Enhanced Visual Tracking

Our research is focused on the development of an at-home health care biomonitoring mobile robot for the people in demand. Main task of the robot is to detect and track a designated subject while recognizing his/her activity for analysis and to provide warning in an emergency. In order to push forwar...

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Main Authors: Nevrez Imamoglu, Enrique Dorronzoro, Zhixuan Wei, Huangjun Shi, Masashi Sekine, José González, Dongyun Gu, Weidong Chen, Wenwei Yu
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/280207
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author Nevrez Imamoglu
Enrique Dorronzoro
Zhixuan Wei
Huangjun Shi
Masashi Sekine
José González
Dongyun Gu
Weidong Chen
Wenwei Yu
author_facet Nevrez Imamoglu
Enrique Dorronzoro
Zhixuan Wei
Huangjun Shi
Masashi Sekine
José González
Dongyun Gu
Weidong Chen
Wenwei Yu
author_sort Nevrez Imamoglu
collection DOAJ
description Our research is focused on the development of an at-home health care biomonitoring mobile robot for the people in demand. Main task of the robot is to detect and track a designated subject while recognizing his/her activity for analysis and to provide warning in an emergency. In order to push forward the system towards its real application, in this study, we tested the robustness of the robot system with several major environment changes, control parameter changes, and subject variation. First, an improved color tracker was analyzed to find out the limitations and constraints of the robot visual tracking considering the suitable illumination values and tracking distance intervals. Then, regarding subject safety and continuous robot based subject tracking, various control parameters were tested on different layouts in a room. Finally, the main objective of the system is to find out walking activities for different patterns for further analysis. Therefore, we proposed a fast, simple, and person specific new activity recognition model by making full use of localization information, which is robust to partial occlusion. The proposed activity recognition algorithm was tested on different walking patterns with different subjects, and the results showed high recognition accuracy.
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institution Kabale University
issn 2356-6140
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language English
publishDate 2014-01-01
publisher Wiley
record_format Article
series The Scientific World Journal
spelling doaj-art-7ebf53b9f7b2426cbea6125914f7ea7a2025-08-20T03:35:48ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/280207280207Development of Robust Behaviour Recognition for an at-Home Biomonitoring Robot with Assistance of Subject Localization and Enhanced Visual TrackingNevrez Imamoglu0Enrique Dorronzoro1Zhixuan Wei2Huangjun Shi3Masashi Sekine4José González5Dongyun Gu6Weidong Chen7Wenwei Yu8Graduate School of Engineering, Chiba University, Chiba 263-8522, JapanResearch Center for Frontier Medical Engineering, Chiba University, Chiba 263-8522, JapanInstitute of Robotics and Intelligent Information Processing, Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, ChinaDepartment of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, ChinaGraduate School of Engineering, Chiba University, Chiba 263-8522, JapanSpanish National Research Council, Bioengineering Group, 28500 Madrid, SpainDepartment of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, ChinaInstitute of Robotics and Intelligent Information Processing, Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, ChinaResearch Center for Frontier Medical Engineering, Chiba University, Chiba 263-8522, JapanOur research is focused on the development of an at-home health care biomonitoring mobile robot for the people in demand. Main task of the robot is to detect and track a designated subject while recognizing his/her activity for analysis and to provide warning in an emergency. In order to push forward the system towards its real application, in this study, we tested the robustness of the robot system with several major environment changes, control parameter changes, and subject variation. First, an improved color tracker was analyzed to find out the limitations and constraints of the robot visual tracking considering the suitable illumination values and tracking distance intervals. Then, regarding subject safety and continuous robot based subject tracking, various control parameters were tested on different layouts in a room. Finally, the main objective of the system is to find out walking activities for different patterns for further analysis. Therefore, we proposed a fast, simple, and person specific new activity recognition model by making full use of localization information, which is robust to partial occlusion. The proposed activity recognition algorithm was tested on different walking patterns with different subjects, and the results showed high recognition accuracy.http://dx.doi.org/10.1155/2014/280207
spellingShingle Nevrez Imamoglu
Enrique Dorronzoro
Zhixuan Wei
Huangjun Shi
Masashi Sekine
José González
Dongyun Gu
Weidong Chen
Wenwei Yu
Development of Robust Behaviour Recognition for an at-Home Biomonitoring Robot with Assistance of Subject Localization and Enhanced Visual Tracking
The Scientific World Journal
title Development of Robust Behaviour Recognition for an at-Home Biomonitoring Robot with Assistance of Subject Localization and Enhanced Visual Tracking
title_full Development of Robust Behaviour Recognition for an at-Home Biomonitoring Robot with Assistance of Subject Localization and Enhanced Visual Tracking
title_fullStr Development of Robust Behaviour Recognition for an at-Home Biomonitoring Robot with Assistance of Subject Localization and Enhanced Visual Tracking
title_full_unstemmed Development of Robust Behaviour Recognition for an at-Home Biomonitoring Robot with Assistance of Subject Localization and Enhanced Visual Tracking
title_short Development of Robust Behaviour Recognition for an at-Home Biomonitoring Robot with Assistance of Subject Localization and Enhanced Visual Tracking
title_sort development of robust behaviour recognition for an at home biomonitoring robot with assistance of subject localization and enhanced visual tracking
url http://dx.doi.org/10.1155/2014/280207
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