[go: up one dir, main page]

Razi et al., 2023 - Google Patents

Deep learning serves traffic safety analysis: A forward‐looking review

Razi et al., 2023

View PDF
Document ID
1106938549836438915
Author
Razi A
Chen X
Li H
Wang H
Russo B
Chen Y
Yu H
Publication year
Publication venue
IET Intelligent Transport Systems

External Links

Snippet

This paper explores deep learning (DL) methods that are used or have the potential to be used for traffic video analysis, emphasising driving safety for both autonomous vehicles and human‐operated vehicles. A typical processing pipeline is presented, which can be used to …
Continue reading at ietresearch.onlinelibrary.wiley.com (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00771Recognising scenes under surveillance, e.g. with Markovian modelling of scene activity
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00791Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30781Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F17/30784Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre
    • G06F17/30799Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre using low-level visual features of the video content
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/20Image acquisition
    • G06K9/32Aligning or centering of the image pick-up or image-field
    • G06K9/3233Determination of region of interest
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/20Analysis of motion
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled

Similar Documents

Publication Publication Date Title
Razi et al. Deep learning serves traffic safety analysis: A forward‐looking review
Huang et al. Intelligent intersection: Two-stream convolutional networks for real-time near-accident detection in traffic video
Wu et al. An explainable and efficient deep learning framework for video anomaly detection
Murthy et al. ObjectDetect: A Real‐Time Object Detection Framework for Advanced Driver Assistant Systems Using YOLOv5
Zhang et al. City brain: practice of large‐scale artificial intelligence in the real world
US8294763B2 (en) Method for building and extracting entity networks from video
Loce et al. Computer vision in roadway transportation systems: a survey
Azfar et al. Deep learning-based computer vision methods for complex traffic environments perception: A review
Roka et al. Anomaly behavior detection analysis in video surveillance: a critical review
Youssef et al. Automatic vehicle counting and tracking in aerial video feeds using cascade region-based convolutional neural networks and feature pyramid networks
Xiang et al. Multi-sensor fusion algorithm in cooperative vehicle-infrastructure system for blind spot warning
Anisha et al. Automated vehicle to vehicle conflict analysis at signalized intersections by camera and LiDAR sensor fusion
Ka et al. Study on the framework of intersection pedestrian collision warning system considering pedestrian characteristics
Athanesious et al. Detecting abnormal events in traffic video surveillance using superorientation optical flow feature
Lee et al. Probabilistic context integration‐based aircraft behaviour intention classification at airport ramps
Abbas et al. Vision based intelligent traffic light management system using Faster R‐CNN
Liu et al. Cooperative and comprehensive multi-task surveillance sensing and interaction system empowered by edge artificial intelligence
Liu et al. MDFD2-DETR: A Real-Time Complex Road Object Detection Model Based on Multi-Domain Feature Decomposition and De-Redundancy
Dharan et al. A comprehensive survey on machine learning techniques to mobilize multi-camera network for smart surveillance
Zarei et al. Real‐time vehicle detection using segmentation‐based detection network and trajectory prediction
Qiu et al. Salient Object Detection in Traffic Scene through the TSOD10K Dataset
Wu et al. To turn or not to turn, safecross is the answer
Gao et al. Whether and how congested is a road? Indices, updating strategy and a vision‐based detection framework
Ji et al. An expert ensemble for detecting anomalous scenes, interactions, and behaviors in autonomous driving
Mane et al. A research survey on real-time intelligent traffic system