Movatterモバイル変換


[0]ホーム

URL:


Mahajan et al., 2023 - Google Patents

Treating noise and anomalies in vehicle trajectories from an experiment with a swarm of drones

Mahajan et al., 2023

Document ID
7519615789249791995
Author
Mahajan V
Barmpounakis E
Alam M
Geroliminis N
Antoniou C
Publication year
Publication venue
IEEE Transactions on Intelligent Transportation Systems

External Links

Snippet

Unmanned aerial systems, known as “drones,” are relatively new in collecting traffic data. Data from drone videography can have potential applications for traffic research. Drones can record the vehicles from their aerial point-of-view and provide their naturalistic driving …
Continue reading atieeexplore.ieee.org (other versions)

Classifications

The classifications are assigned by a computer and are not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the classifications listed.
    • 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
    • G06K9/00624Recognising 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
    • G06K9/36Image 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
    • G06K9/00496Recognising patterns in signals and combinations thereof
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • 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
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/0104Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125Traffic data processing
    • G08G1/0129Traffic data processing for creating historical data or processing based on historical data
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing

Similar Documents

PublicationPublication DateTitle
Kim et al.Extracting vehicle trajectories using unmanned aerial vehicles in congested traffic conditions
Mahajan et al.Treating noise and anomalies in vehicle trajectories from an experiment with a swarm of drones
Fard et al.A new methodology for vehicle trajectory reconstruction based on wavelet analysis
CN114821421B (en) A method and system for detecting abnormal traffic behavior
Matarazzo et al.Crowdsourcing bridge dynamic monitoring with smartphone vehicle trips
Oucheikh et al.Deep real-time anomaly detection for connected autonomous vehicles
Wang et al.A traffic prediction model based on multiple factors
US20170336215A1 (en)Classifying entities in digital maps using discrete non-trace positioning data
CN105989614A (en)Dangerous object detection method fusing multi-source visual information
Saha et al.Developing a framework for vehicle detection, tracking and classification in traffic video surveillance
Satzoda et al.Drive analysis using lane semantics for data reduction in naturalistic driving studies
Hu et al.Detecting socially abnormal highway driving behaviors via recurrent graph attention networks
Chetouane et al.On the application of clustering for extracting driving scenarios from vehicle data
Zou et al.Traffic incident classification at intersections based on image sequences by HMM/SVM classifiers
Gong et al.Heterogeneous traffic flow detection using CAV-based sensor with I-GAIN
Khasawneh et al.Multilevel learning for enhanced traffic congestion prediction using anomaly detection and ensemble learning
Lushan et al.Supervising vehicle using pattern recognition: Detecting unusual behavior using machine learning algorithms
Priyadharshini et al.Vehicle data aggregation from highway video of madurai city using convolution neural network
Tang et al.Application of CNN‐LSTM Model for Vehicle Acceleration Prediction Using Car‐following Behavior Data
Zhang et al.Segmentation is tracking: Spatial-temporal map vehicle trajectory reconstruction and validation
CN119903439B (en) Multi-category unsafe driving behavior detection method, device and computer equipment
Muâ et al.Classifying Vehicle Types from Video Streams for Traffic Flow Analysis Systems
Tripathi et al.Driver activity monitoring using MobileNets
Zhang et al.Enhancing Vehicle Trajectory Quality: A Two‐Step Data Reconstruction Method Using Wavelet Transform and Normal Acceleration Value
AbdelhalimA real-time computer vision based framework for urban traffic safety assessment and driver behavior modeling using virtual traffic lanes

[8]
ページ先頭

©2009-2025 Movatter.jp