ArticleSensors (Basel, Switzerland)2021
Real-Time Action Recognition System for Elderly People Using Stereo Depth Camera.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- AI-Driven Activity of Daily Living Monitoring: A Comprehensive Review of Ambient, Wearable, and Fusion-Based Sensing Technologies.Annals of biomedical engineering · 2026Review
- Enhancing single shot unsupervised domain adaptation for inter-camera person re-identification.Scientific reports · 2026Article
- Leveraging assistive technology for visually impaired people through optimal deep transfer learning based object detection model.Scientific reports · 2025Article
- Article
- Action Recognition of Taekwondo Unit Actions Using Action Images Constructed with Time-Warped Motion Profiles.Sensors (Basel, Switzerland) · 2024Article
- TCN-attention-HAR: human activity recognition based on attention mechanism time convolutional network.Scientific reports · 2024Article
- Artificial Intelligence Procedure for the Screening of Genetic Syndromes Based on Voice Characteristics.Bioengineering (Basel, Switzerland) · 2023Article
- Human Action Recognition in Smart Living Services and Applications: Context Awareness, Data Availability, Personalization, and Privacy.Sensors (Basel, Switzerland) · 2023Review
- Review on Human Action Recognition in Smart Living: Sensing Technology, Multimodality, Real-Time Processing, Interoperability, and Resource-Constrained Processing.Sensors (Basel, Switzerland) · 2023Review
- Exploring Older Adults' Willingness to Install Home Surveil-Lance Systems in Taiwan: Factors and Privacy Concerns.Healthcare (Basel, Switzerland) · 2023Article
- HMM-Based Action Recognition System for Elderly Healthcare by Colorizing Depth Map.International journal of environmental research and public health · 2022Article
- Mathematical Criteria for a Priori Performance Estimation of Activities of Daily Living Recognition.Sensors (Basel, Switzerland) · 2022Article
- Design of Sports Rehabilitation Training System Based on EEMD Algorithm.Computational intelligence and neuroscience · 2022Article
- Edge Detection-Based Feature Extraction for the Systems of Activity Recognition.Computational intelligence and neuroscience · 2022Article
- Human Action Recognition: A Paradigm of Best Deep Learning Features Selection and Serial Based Extended Fusion.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.