Real-Time Action Recognition System for Elderly People Using Stereo Depth Camera

Zin, Thi Thi; Htet, Ye; Akagi, Yuya; Tamura, Hiroki; Kondo, Kazuhiro; Araki, Sanae; Chosa, Etsuo

doi:10.3390/s21175895

Open AccessArticle

Real-Time Action Recognition System for Elderly People Using Stereo Depth Camera

by

Thi Thi Zin

^1,*

,

Ye Htet

¹

,

Yuya Akagi

¹,

Hiroki Tamura

¹

,

Kazuhiro Kondo

²,

Sanae Araki

² and

Etsuo Chosa

²

¹

Graduate School of Engineering, University of Miyazaki, Miyazaki 889-2192, Japan

²

Faculty of Medicine, University of Miyazaki, Miyazaki 889-1692, Japan

^*

Author to whom correspondence should be addressed.

Sensors 2021, 21(17), 5895; https://doi.org/10.3390/s21175895

Submission received: 28 July 2021 / Revised: 28 August 2021 / Accepted: 30 August 2021 / Published: 1 September 2021

(This article belongs to the Special Issue Sensor-Based Human Activity Monitoring)

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Abstract

Smart technologies are necessary for ambient assisted living (AAL) to help family members, caregivers, and health-care professionals in providing care for elderly people independently. Among these technologies, the current work is proposed as a computer vision-based solution that can monitor the elderly by recognizing actions using a stereo depth camera. In this work, we introduce a system that fuses together feature extraction methods from previous works in a novel combination of action recognition. Using depth frame sequences provided by the depth camera, the system localizes people by extracting different regions of interest (ROI) from UV-disparity maps. As for feature vectors, the spatial-temporal features of two action representation maps (depth motion appearance (DMA) and depth motion history (DMH) with a histogram of oriented gradients (HOG) descriptor) are used in combination with the distance-based features, and fused together with the automatic rounding method for action recognition of continuous long frame sequences. The experimental results are tested using random frame sequences from a dataset that was collected at an elder care center, demonstrating that the proposed system can detect various actions in real-time with reasonable recognition rates, regardless of the length of the image sequences.

Keywords: ambient assisted living; stereo depth camera; UV-disparity maps; depth map features; depth motion appearance; depth motion history; histogram of oriented gradients; action recognition

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MDPI and ACS Style

Zin, T.T.; Htet, Y.; Akagi, Y.; Tamura, H.; Kondo, K.; Araki, S.; Chosa, E. Real-Time Action Recognition System for Elderly People Using Stereo Depth Camera. Sensors 2021, 21, 5895. https://doi.org/10.3390/s21175895

AMA Style

Zin TT, Htet Y, Akagi Y, Tamura H, Kondo K, Araki S, Chosa E. Real-Time Action Recognition System for Elderly People Using Stereo Depth Camera. Sensors. 2021; 21(17):5895. https://doi.org/10.3390/s21175895

Chicago/Turabian Style

Zin, Thi Thi, Ye Htet, Yuya Akagi, Hiroki Tamura, Kazuhiro Kondo, Sanae Araki, and Etsuo Chosa. 2021. "Real-Time Action Recognition System for Elderly People Using Stereo Depth Camera" Sensors 21, no. 17: 5895. https://doi.org/10.3390/s21175895

APA Style

Zin, T. T., Htet, Y., Akagi, Y., Tamura, H., Kondo, K., Araki, S., & Chosa, E. (2021). Real-Time Action Recognition System for Elderly People Using Stereo Depth Camera. Sensors, 21(17), 5895. https://doi.org/10.3390/s21175895

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Real-Time Action Recognition System for Elderly People Using Stereo Depth Camera

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