Edge Video Analytics for Public Safety: A Review
- 30 July 2019
- journal article
- review article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in Proceedings of the IEEE
- Vol. 107 (8), 1675-1696
- https://doi.org/10.1109/jproc.2019.2925910
Abstract
With the installation of enormous public safety and transportation infrastructure cameras, video analytics has come to play an essential part in public safety. Typically, video analytics is to collectively leverage the advanced computer vision (CV) and artificial intelligence (AI) to solve the four-W problem. That is to identify Who has done something (What) at a specific place (Where) at some time (When). According to the difference of latency requirements, video analytics can be applied to postevent retrospective analysis, such as archive management, search, forensic investigation and real-time live video stream analysis, such as situation awareness, alerting, and interested object (criminal suspect/missing vehicle) detection. The latter is characterized as having higher requirements on hardware resources as the sophisticated image processing algorithms under the hood. However, analyzing large-scale live video streams on the Cloud is impractical as the edge solution that conducts the video analytics on (or close to) the camera provides a silvering light. Analyzing live video streams on the edge is not trivial due to the constrained hardware resources on edge. The AI-dominated video analytics requires higher bandwidth, consumes considerable CPU/GPU resources for processing, and demands larger memory for caching. In this paper, we review the applications, algorithms, and solutions that have been proposed recently to facilitate edge video analytics for public safety.Keywords
Funding Information
- National Natural Science Foundation of China (61572001, 61702004, 61872001)
- Key Technology R&D Program of Anhui Province (1704d0802193)
- Natural Science Foundation of Anhui Province (1708085QF160)
- National Science Foundation (CNS1741635)
This publication has 109 references indexed in Scilit:
- Covariance matrix-based fire and flame detection method in videoMachine Vision and Applications, 2011
- An Unmanned Aircraft System for Automatic Forest Fire Monitoring and MeasurementJournal of Intelligent & Robotic Systems, 2011
- Architecture for a helicopter-based unmanned aerial systems wildfire surveillance systemGeocarto International, 2011
- IBM smart surveillance system (S3): event based video surveillance system with an open and extensible frameworkMachine Vision and Applications, 2008
- Traffic-Incident Detection-Algorithm Based on Nonparametric RegressionIEEE Transactions on Intelligent Transportation Systems, 2005
- Learning to detect objects in images via a sparse, part-based representationIEEE Transactions on Pattern Analysis and Machine Intelligence, 2004
- Applications of video-content analysis and retrievalIEEE MultiMedia, 2002
- Neural network-based face detectionIEEE Transactions on Pattern Analysis and Machine Intelligence, 1998
- Eigenfaces vs. Fisherfaces: recognition using class specific linear projectionIEEE Transactions on Pattern Analysis and Machine Intelligence, 1997
- Boosting a Weak Learning Algorithm by MajorityInformation and Computation, 1995