Optimization of an Artificial Intelligence Database and Camera Installation for Recognition of Risky Passenger Behavior in Railway Vehicles
Source abstract
Abstract
Urban railways are vital means of public transportation in Korea. More than 30% of metropolitan residents use the railways, and this proportion is expected to increase. To enhance safety, the government has mandated the insta... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: IoT and GPS-based Vehicle Safety Systems · Risk and Safety Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (29)
Show source-provided references
1. W. Kay et al., “The kinetics human action video dataset,” 2017, arXiv:1705.06950.
2. A dataset of 101 human action classes from videos in the wild
3. G. A. Sigurdsson, G. Varol, X. Wang, A. Farhadi, I. Laptev and A. Gupta, “Hollywood in homes: Crowdsourcing data collection for activity understanding,” 2016, arXiv:1604.01753.10.1007/978-3-319-46448-0_31 ↗
4. HMDB: A large video database for human motion recognition
5. AVA: A video dataset of spatio-temporally localized atomic visual actions
6. Patterns of behavioral engagement in an online English language course: Cluster analysis
7. Beinborn · Cognitive Plausibility in Natural Language Processing. Synthesis Lectures on Human Language Technologies · 2024
8. Social media- and internet-based disease surveillance for public health10.1146/annurev-publhealth-040119-094402 ↗
9. Valuing health surveillance as an information system: Interdisciplinary insights
10. Towards single 2D image-level self-supervision for 3D human pose and shape estimation10.3390/app11209724 ↗
11. A study of vision based human motion recognition and analysis10.4018/IJACI.2016070104 ↗
12. Multi-camera-based human activity recognition for human-robot collaboration in construction10.3390/s23156997 ↗
13. Improving the robustness of object detection through a multi-casmera-based fusion algorithm using fuzzy logic10.3389/frai.2021.638951 ↗
14. Optimal camera placement for automated surveillance tasks10.1007/s10846-007-9164-7 ↗
15. Multi-camera positioning to optimize task observability
16. CAMOT: Camera angle-aware multi-object tracking
17. Study on factors for passenger risk in railway vehicle
18. Deep-learning-based action recognition with 3D skeleton: A survey10.1049/cit2.12014 ↗
19. B. Ren, M. Liu, R. Ding, and H. Liu, “A survey on 3D skeleton-based action recognition using learning method,” 2020, arXiv:2002.05907v1.
20. Fall detection and activity recognition using human skeleton features10.1109/ACCESS.2021.3061626 ↗
21. Reconstruction of articulated objects from point correspondences in a single uncalibrated image10.1006/cviu.2000.0878 ↗
22. Deep learning for human activity recognition on 3D human skeleton: Survey and comparative study10.3390/s23115121 ↗
23. Co-occurrence feature learning for skeleton-based action recognition using regularized deep LSTM networks
24. Convolutional neural networks and long short-term memory for skeleton-based human activity and hand gesture recognition10.1016/j.patcog.2017.10.033 ↗
25. FCOS: Fully convolutional one-stage object detection
26. Classification-based multi-task learning for efficient pose estimation network
27. N. Aharon, R. Orfaig, and B. Bobrovsky, “BoT-SORT: Robust associations multi-pedestrian tracking,” 2022, arXiv:2206.14651.
28. VFP290K: A large-scale benchmark dataset for vision-based fallen person detection
29. Action recognition for depth video using multi-view dynamic images10.1016/j.ins.2018.12.050 ↗