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Sensors 2014, 14(7), 11735-11759; doi:10.3390/s140711735
Article

A Depth Video Sensor-Based Life-Logging Human Activity Recognition System for Elderly Care in Smart Indoor Environments

1
, 2
 and 1,*
Received: 29 March 2014; in revised form: 24 June 2014 / Accepted: 27 June 2014 / Published: 2 July 2014
(This article belongs to the Section Physical Sensors)
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Abstract: Recent advancements in depth video sensors technologies have made human activity recognition (HAR) realizable for elderly monitoring applications. Although conventional HAR utilizes RGB video sensors, HAR could be greatly improved with depth video sensors which produce depth or distance information. In this paper, a depth-based life logging HAR system is designed to recognize the daily activities of elderly people and turn these environments into an intelligent living space. Initially, a depth imaging sensor is used to capture depth silhouettes. Based on these silhouettes, human skeletons with joint information are produced which are further used for activity recognition and generating their life logs. The life-logging system is divided into two processes. Firstly, the training system includes data collection using a depth camera, feature extraction and training for each activity via Hidden Markov Models. Secondly, after training, the recognition engine starts to recognize the learned activities and produces life logs. The system was evaluated using life logging features against principal component and independent component features and achieved satisfactory recognition rates against the conventional approaches. Experiments conducted on the smart indoor activity datasets and the MSRDailyActivity3D dataset show promising results. The proposed system is directly applicable to any elderly monitoring system, such as monitoring healthcare problems for elderly people, or examining the indoor activities of people at home, office or hospital.
Keywords: depth video sensors; human activity recognition (HAR); body joints points; Hidden Markov Models; life-logging system depth video sensors; human activity recognition (HAR); body joints points; Hidden Markov Models; life-logging system
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Jalal, A.; Kamal, S.; Kim, D. A Depth Video Sensor-Based Life-Logging Human Activity Recognition System for Elderly Care in Smart Indoor Environments. Sensors 2014, 14, 11735-11759.

AMA Style

Jalal A, Kamal S, Kim D. A Depth Video Sensor-Based Life-Logging Human Activity Recognition System for Elderly Care in Smart Indoor Environments. Sensors. 2014; 14(7):11735-11759.

Chicago/Turabian Style

Jalal, Ahmad; Kamal, Shaharyar; Kim, Daijin. 2014. "A Depth Video Sensor-Based Life-Logging Human Activity Recognition System for Elderly Care in Smart Indoor Environments." Sensors 14, no. 7: 11735-11759.



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