| Autor: |
Thi Thi Zin, Ye Htet, Yuya Akagi, Hiroki Tamura, Kazuhiro Kondo, Sanae Araki, Etsuo Chosa |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Sensors, Vol 21, Iss 17, p 5895 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
1424-8220 |
| DOI: |
10.3390/s21175895 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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