A survey of vision-based vehicle detection and tracking techniques in ITS

No abstract is available for this paper.

• Publication year

  2013

• Venue

  Proceedings of 2013 IEEE International Conference on Vehicular Electronics and Safety

• Publication date

  2013-07-28

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.1109/ICVES.2013.6619606
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• A vehicle detection approach based on multi-features fusion in the fisheye images

  2011cited by this paper
• Data-Driven Intelligent Transportation Systems: A Survey

  2011cited by this paper
• A Review of Computer Vision Techniques for the Analysis of Urban Traffic

  2011influential reference
• Vehicle detection and tracking with low-angle cameras

  2010cited by this paper
• Background Subtraction

  2009influential reference
• Predicting high resolution image edges with a generic, adaptive, 3-D vehicle model

  2009cited by this paper
• A stochastic graph grammar for compositional object representation and recognition

  2009cited by this paper
• A Robust Technique for Background Subtraction in Traffic Video

  2009cited by this paper
• Learning coupled conditional random field for image decomposition with application on object categorization

  2008cited by this paper
• MCMC Particle Filter for Real-Time Visual Tracking of Vehicles

  2008cited by this paper
• Viewpoint-independent object class detection using 3D Feature Maps

  2008cited by this paper
• Robust tracking of spatial related components

  2008cited by this paper
• 3D LayoutCRF for Multi-View Object Class Recognition and Segmentation

  2007cited by this paper
• Vehicle Detection Using Normalized Color and Edge Map

  2007cited by this paper
• Video-based detection of street-parking violation

  2007cited by this paper
• Robust classification and tracking of vehicles in traffic video streams

  2006cited by this paper
• Moving Object Detecting Using Gradient Information, Three-Frame-Differencing and Connectivity Testing

  2006cited by this paper
• Extracting Roadway Background Image

  2006cited by this paper
• On-road vehicle detection: a review

  2006cited by this paper
• The Layout Consistent Random Field for Recognizing and Segmenting Partially Occluded Objects

  2006cited by this paper
• Real time classification and tracking of multiple vehicles in highways

  2005cited by this paper
• A computer vision system for the detection and classification of vehicles at urban road intersections

  2005cited by this paper
• Vehicle detection combining gradient analysis and AdaBoost classification

  2005influential reference
• A system for traffic sign detection, tracking, and recognition using color, shape, and motion information

  2005influential reference
• Kernel-Based Object Tracking

  2003cited by this paper
• Bayesian network based computer vision algorithm for traffic monitoring using video

  2003cited by this paper
• An adaptive color-based particle filter

  2003cited by this paper
• IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, VOL. 3, NO. 1, MARCH 2002 37 Detection and Classification of Vehicles

  2002cited by this paper
• Mean Shift: A Robust Approach Toward Feature Space Analysis

  2002cited by this paper
• A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking

  2002cited by this paper
• Vision-based vehicle detection and tracking method for forward collision warning in automobiles

  2002cited by this paper
• A New Approach to Linear Filtering and Prediction Problems

  2002cited by this paper
• Color modeling by spherical influence field in sensing driving environment

  2000cited by this paper
• A robust background subtraction method for changing background

  2000cited by this paper
• Learning Patterns of Activity Using Real-Time Tracking

  2000cited by this paper
• Scene analysis and organization of behavior in driver assistance systems

  2000cited by this paper
• A tunable algorithm to update a reference image

  2000cited by this paper
• A Robust Background Subtraction and Shadow Detection

  1999cited by this paper
• Vehicle Detection under Day and Night Illumination

  1999cited by this paper
• Real-time stereo processing, obstacle detection, and terrain estimation from vehicle-mounted stereo cameras

  1998cited by this paper
• Revised Definition of Optical Flow: Integration of Radiometric and Geometric Cues for Dynamic Scene Analysis

  1998cited by this paper
• GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection

  1998cited by this paper
• A Texture-based Object Detection and an adaptive Model-based Classification

  1998cited by this paper
• Color-based tracking of heads and other mobile objects at video frame rates

  1997cited by this paper
• A real-time oriented system for vehicle detection

  1997cited by this paper
• Artificial neural networks in real-time car detection and tracking applications

  1996cited by this paper
• VEHICLE DETECTION AND RECOGNITION IN GREYSCALE IMAGERY

  1995cited by this paper
• The computation of optical flow

  1995cited by this paper
• Obstacle Detection By Vision System For An Autonomous Vehicle

  1993cited by this paper
• Shadow and rhythm as sign patterns of obstacle detection

  1993cited by this paper
• Symmetry-based recognition of vehicle rears

  1991cited by this paper
• Using symmetry for detecting and locating objects in a picture

  1989cited by this paper
• Change detection for target detection and classification in video sequences

  1988cited by this paper
• A sensor for control of arterials and networks

  1980cited by this paper
• The estimation of the gradient of a density function, with applications in pattern recognition

  1975cited by this paper
• Textural Features for Image Classification

  1973cited by this paper

• Performance efficient vehicle detection and tracking based on pyramid pooling network: a review and implementation

  2025cites this paper
• Performance Comparison between Deep Learning and Machine Learning Algorithms in Vehicle Detection

  2024cites this paper
• Open Urban mmWave Radar and Camera Vehicle Classification Dataset for Traffic Monitoring

  2024cites this paper
• Capturing the true bounding boxes: vehicle kinematic data extraction using unmanned aerial vehicles

  2024cites this paper
• Analysis of Magnetic Signatures for Vehicle Detection Using Dual-Axis Magneto-Impedance Sensors

  2024cites this paper
• A vision-based real-time traffic flow monitoring system for road intersections

  2023cites this paper
• Last Decade in Vehicle Detection and Classification: A Comprehensive Survey

  2022cites this paper
• A Review of Vision-Based Traffic Semantic Understanding in ITSs

  2022cites this paper
• Traffic density estimation via a multi-level feature fusion network

  2022cites this paper
• LITERATURE SURVEY ON CAR AND PEDESTRIAN TRACKING SYSTEM

  2021cites this paper
• CAROM - Vehicle Localization and Traffic Scene Reconstruction from Monocular Cameras on Road Infrastructures

  2021cites this paper
• Vehicle Classification and Counting System Using YOLO Object Detection Technology

  2021cites this paper
• A Multi-Loop Vehicle-Counting Method under Gray Mode and RGB Mode

  2021cites this paper
• Real-time vehicle counting in complex scene for traffic flow estimation using multi-level convolutional neural network

  2021cites this paper
• Video Based Vehicle Counting Using Deep Learning Algorithms

  2020cites this paper
• Performance Metrics and Validation Methods for Vehicle Position Estimators

  2020cites this paper
• Vehicle detection in intelligent transport system under a hazy environment: a survey

  2020cites this paper
• System for Detection of Vehicles in Multiple Video Streams in Road Infrastructure Monitoring

  2020cites this paper
• Robust Vehicle Detection and Counting Algorithm Adapted to Complex Traffic Environments with Sudden Illumination Changes and Shadows

  2020cites this paper
• Two-Wheeled Vehicle Detection Using Two-Step and Single-Step Deep Learning Models

  2020cites this paper
• Automatic Vehicles Detection, Classification and Counting Techniques / Survey

  2020influential citation
• A Multi-target Edge Service Approach to Real-time Image Object Detection

  2020cites this paper
• Video-Based Vehicle Counting Framework

  2019cites this paper
• EFFICIENT APPROACH FOR VEHICLE COUNTING BASED ON DEEP CONVOLUTIONAL NEURAL NETWORKS

  2019cites this paper
• Accurate Vehicle Counting Approach Based on Deep Neural Networks

  2019cites this paper
• A Comparative Study of Vehicle Detection Methods in a Video Sequence

  2019cites this paper
• Real Time Detection and Tracking of a Model Car using Kalman Filter

  2019cites this paper
• Improved Turning Angle Calculation for an Unmanned Ground Vehicle

  2019cites this paper
• Real-Time Tracking and Lane Line Detection Technique for an Autonomous Ground Vehicle System

  2019cites this paper
• A Motion Detection Algorithm Integrating Foreground Matching into Gaussian Mixture Modeling

  2018cites this paper
• Real-time vehicle detection and counting in complex traffic scenes using background subtraction model with low-rank decomposition

  2017cites this paper
• Smart Transportation Systems: Architecture, Enabling Technologies, and Open Issues

  2017cites this paper
• Vehicle detection, counting and classification in various conditions

  2016cites this paper
• Fast spatio-temporal stereo matching for advanced driver assistance systems

  2016cites this paper
• Multisensorial obstacles detection and classification for ADAS and autonomous driving

  2016cites this paper
• Vision-Based 3D Motion Estimation for On-Orbit Proximity Satellite Tracking and Navigation

  2015cites this paper
• Observation of Vehicle-Related Events on Highways Using OpenCV

  2015cites this paper
• Real-time moving vehicle detection, tracking, and counting system implemented with OpenCV

  2014cites this paper
• Crossroad Traffic Surveillance Using Superpixel Tracking and Vehicle Trajectory Analysis

  2014cites this paper