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Found 14 papers, 4 papers with code
Evaluating the Effectiveness of Video Anomaly Detection in the Wild: Online Learning and Inference for Real-world Deployment
Video Anomaly Detection (VAD) identifies unusual activities in video streams, a key technology with broad applications ranging from surveillance to healthcare.
Integrating AI into CCTV Systems: A Comprehensive Evaluation of Smart Video Surveillance in Community Space
This article presents an AI-enabled Smart Video Surveillance (SVS) designed to enhance safety in community spaces such as educational and recreational areas, and small businesses.
VegaEdge: Edge AI Confluence Anomaly Detection for Real-Time Highway IoT-Applications
On top of that, we present VegaEdge - a sophisticated AI confluence designed for real-time security and surveillance applications in modern highway settings through edge-centric IoT-embedded platforms equipped with our anomaly detection approach.
VT-Former: An Exploratory Study on Vehicle Trajectory Prediction for Highway Surveillance through Graph Isomorphism and Transformer
This study seeks to explore both the advantages and the limitations inherent in combining transformer architecture with graphs for VTP.
Real-World Community-in-the-Loop Smart Video Surveillance -- A Case Study at a Community College
This paper presents a case study for designing and deploying smart video surveillance systems based on a real-world testbed at a community college.
A POV-based Highway Vehicle Trajectory Dataset and Prediction Architecture
We introduce the \emph{Carolinas Highway Dataset (CHD\footnote{\emph{CHD} available at: \url{https://github. com/TeCSAR-UNCC/Carolinas\_Dataset}})}, a vehicle trajectory, detection, and tracking dataset.
Understanding the Challenges and Opportunities of Pose-based Anomaly Detection
In this work, we analyze and quantify the characteristics of two well-known video anomaly datasets to better understand the difficulties of pose-based anomaly detection.
Understanding Policy and Technical Aspects of AI-Enabled Smart Video Surveillance to Address Public Safety
Finally, we propose quantitative and qualitative metrics to evaluate intelligent video surveillance systems.
Ancilia: Scalable Intelligent Video Surveillance for the Artificial Intelligence of Things
With the advancement of vision-based artificial intelligence, the proliferation of the Internet of Things connected cameras, and the increasing societal need for rapid and equitable security, the demand for accurate real-time intelligent surveillance has never been higher.
Understanding Ethics, Privacy, and Regulations in Smart Video Surveillance for Public Safety
These systems are used to make the policing and monitoring systems more efficient and improve public safety.
CHAD: Charlotte Anomaly Dataset
In addition to frame-level anomaly labels, CHAD is the first anomaly dataset to include bounding box, identity, and pose annotations for each actor.
Pishgu: Universal Path Prediction Network Architecture for Real-time Cyber-physical Edge Systems
These real-world CPS applications need a robust, lightweight path prediction that can provide a universal network architecture for multiple subjects (e. g., pedestrians and vehicles) from different perspectives.
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Trajectory Prediction
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A Survey of Graph-based Deep Learning for Anomaly Detection in Distributed Systems
Anomaly detection is a crucial task in complex distributed systems.
ADG-Pose: Automated Dataset Generation for Real-World Human Pose Estimation
Recent advancements in computer vision have seen a rise in the prominence of applications using neural networks to understand human poses.
