# Review on Action Recognition for Accident Detection in Smart City Transportation Systems

arXiv: https://arxiv.org/abs/2208.09588 · HTML: https://mlsanity.com/paper/2208.09588/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 120 references that are in the map.
- First posted on arXiv 20 Aug 2022.

## Builds on (most cited first, 18 of 18)

- [Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset](https://mlsanity.com/paper/1705.07750/) (2017)
- [Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting](https://mlsanity.com/paper/1506.04214/) (2015)
- [T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction](https://mlsanity.com/paper/1811.05320/) (2018)
- [LSTM: A Search Space Odyssey](https://mlsanity.com/paper/1503.04069/) (2015)
- [The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems](https://mlsanity.com/paper/1810.05642/) (2018)
- [INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps](https://mlsanity.com/paper/1910.03088/) (2019)
- [The ApolloScape Open Dataset for Autonomous Driving and its Application](https://mlsanity.com/paper/1803.06184/) (2018)
- [GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs](https://mlsanity.com/paper/1803.07294/) (2018)
- [Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning](https://mlsanity.com/paper/2008.00334/) (2020)
- [Segmental Spatiotemporal CNNs for Fine-grained Action Segmentation](https://mlsanity.com/paper/1602.02995/) (2016)
- [P-CNN: Pose-based CNN Features for Action Recognition](https://mlsanity.com/paper/1506.03607/) (2015)
- [On the Integration of Optical Flow and Action Recognition](https://mlsanity.com/paper/1712.08416/) (2017)
- [Automatic Operating Room Surgical Activity Recognition for Robot-Assisted Surgery](https://mlsanity.com/paper/2006.16166/) (2020)
- [Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art](https://mlsanity.com/paper/1806.05226/) (2018)
- [Computer Vision-based Accident Detection in Traffic Surveillance](https://mlsanity.com/paper/1911.10037/) (2019)
- [Two-Stream Networks for Lane-Change Prediction of Surrounding Vehicles](https://mlsanity.com/paper/2008.10869/) (2020)
- [Intrusion Detection System in Smart Home Network Using Bidirectional LSTM and Convolutional Neural Networks Hybrid Model](https://mlsanity.com/paper/2105.12096/) (2021)
- [Deep Learning Algorithm for Threat Detection in Hackers Forum (Deep Web)](https://mlsanity.com/paper/2202.01448/) (2022)

## Built on by (most cited first, 8 of 8)

- [Vision-Based Traffic Accident Detection and Anticipation: A Survey](https://mlsanity.com/paper/2308.15985/) (2023)
- [Smart City Transportation: Deep Learning Ensemble Approach for Traffic Accident Detection](https://mlsanity.com/paper/2310.10038/) (2023)
- [Baby Physical Safety Monitoring in Smart Home Using Action Recognition System](https://mlsanity.com/paper/2210.12527/) (2022)
- [AI on the Road: A Comprehensive Analysis of Traffic Accidents and Accident Detection System in Smart Cities](https://mlsanity.com/paper/2307.12128/) (2023)
- [LiteLSTM Architecture Based on Weights Sharing for Recurrent Neural Networks](https://mlsanity.com/paper/2301.04794/) (2023)
- [Big Data and Deep Learning in Smart Cities: A Comprehensive Dataset for AI-Driven Traffic Accident Detection and Computer Vision Systems](https://mlsanity.com/paper/2401.03587/) (2024)
- [Spatial-Temporal Perception with Causal Inference for Naturalistic Driving Action Recognition](https://mlsanity.com/paper/2503.04078/) (2025)
- [Pre-trained Under Noise: A Framework for Robust Bone Fracture Detection in Medical Imaging](https://mlsanity.com/paper/2507.09731/) (2025)

## Abstract (arXiv)

Action detection and public traffic safety are crucial aspects of a safe community and a better society. Monitoring traffic flows in a smart city using different surveillance cameras can play a significant role in recognizing accidents and alerting first responders. The utilization of action recognition (AR) in computer vision tasks has contributed towards high-precision applications in video surveillance, medical imaging, and digital signal processing. This paper presents an intensive review focusing on action recognition in accident detection and autonomous transportation systems for a smart city. In this paper, we focused on AR systems that used diverse sources of traffic video capturing, such as static surveillance cameras on traffic intersections, highway monitoring cameras, drone cameras, and dash-cams. Through this review, we identified the primary techniques, taxonomies, and algorithms used in AR for autonomous transportation and accident detection. We also examined data sets utilized in the AR tasks, identifying the main sources of datasets and features of the datasets. This paper provides potential research direction to develop and integrate accident detection systems for autonomous cars and public traffic safety systems by alerting emergency personnel and law enforcement in the event of road accidents to minimize human error in accident reporting and provide a spontaneous response to victims