• Corpus ID: 18601560

Visual Vehicle Tracking Using An Improved EKF

  title={Visual Vehicle Tracking Using An Improved EKF},
  author={Jian-Guang Lou and Hao Yang and Weiming Hu and Tieniu Tan},
In this paper, a dynamic model of car motion is proposed in which the turn of the steering wheel and the distance between the front and rear wheel are taken into account. Extended Kalman Filter (EKF) is widely used in visual tracking systems. However, because there is no direct link between the behaviour of the driver who controls the motion of the car and the assumed dynamic model, the traditional EKF does not perform well when the car carries out a complicated manoeuvre. In order to reduce… 

Figures from this paper

On Motion Models for Target Tracking in Automotive Applications
In automotive tracking applications, using two separate linear state space models for longitudinal and angular movement of objects is a widely applied simplification. The separation is possible if
A Global Motion Model for Target Tracking in Automotive Applications
  • Markus BührenBin Yang
  • Engineering
    2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07
  • 2007
This paper reviews the drawbacks of the commonly used models and presents a more general motion model for automotive tracking systems and all necessary expressions for an implementation using an extended or unscented Kalman filter are given.
Vehicle parameterization and tracking from traffic videos
This paper presents a method used on high resolution traffic surveillance videos to track and estimate vehicles' state when the cameras are mounted on moderate height structures typically less than 10 meters, which demonstrates robust tracking and state estimation for a variety of vehicle types.
Vehicle tracking using on-line fusion of color and shape features
  • Kai SheG. BebisHaisong GuR. Miller
  • Computer Science
    Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749)
  • 2004
A real-time on-road vehicle tracking method that builds statistical models for the target in color and shape feature spaces and continuously evaluates each of the feature spaces by computing the similarity score between the probabilistic distributions of the target and the model.
Image Filtering of Colored Noise Based on Kalman Filter
This paper presents a core approach to design and develop a real-time based Vehicle Tracking System using Kalman filter. It is used to determine the current location of a target device in terms of
Traffic accident prediction using vehicle tracking and trajectory analysis
A probabilistic model for prediction of traffic accidents using 3D model based vehicle tracking using a fuzzy self-organizing neural network algorithm to learn activity patterns from sample trajectories is proposed.
Ehicle T Racking Using K Alman F Ilter and F Eatures
This paper describes a method, for tracking multiple objects, where the objects are vehicles, and uses the kalman filter and color feature and distance of it from one frame to the next, so the method can distinguish and tracking all vehicles individually.
Traffic accident prediction using 3-D model-based vehicle tracking
A probabilistic model for predicting traffic accidents using three-dimensional (3-D) model-based vehicle tracking is proposed and the effectiveness of the proposed algorithms is shown.
Robust multi-view pedestrian tracking using neural networks
The experimental result shows that the proposed approach yields promising performance on multi-view pedestrian detection and tracking on different benchmark datasets.


Filter for Car Tracking Based on Acceleration and Steering Angle
Experiments show that the CUF is better than the EKF at predicting future positions of the car; and the filter outputs can be used to control the measurement process, leading to improved ability to recover from errors in predictive tracking.
Robust Multiple Car Tracking with Occlusion Reasoning
This work proposes a new approach for tracking vehicles in road traffic scenes using an explicit occlusion reasoning step and employs a contour tracker based on intensity and motion boundaries to obtain robust motion estimates and trajectories for vehicles even in the case of occlusions.
An efficient implementation and evaluation of Reid's multiple hypothesis tracking algorithm for visual tracking
  • I. CoxS. L. Hingorani
  • Computer Science
    Proceedings of 12th International Conference on Pattern Recognition
  • 1994
An efficient implementation of Reid's multiple hypothesis tracking (MHT) algorithm is presented in which the the k-best hypotheses are determined in polynomial time using an algorithm due to Murty
Efficient image gradient based vehicle localization
Novel algorithms for the efficient localization and recognition of traffic in traffic scenes are reported, which eliminate the need for explicit symbolic feature extraction and matching and are very well suited to real-time implementation.
Learning to Track the Visual Motion of Contours
A System for Video Surveillance and Monitoring
An overview of theVSAM system, which uses multiple, cooperative video sensors to provide continuous coverage of people and vehicles in a cluttered environment, is presented.
W/sup 4/: Who? When? Where? What? A real time system for detecting and tracking people
W/sup 4/ is a real time visual surveillance system for detecting and tracking people and monitoring their activities in an outdoor environment that employs a combination of shape analysis and tracking to locate people and their parts and to create models of people's appearance so that they can be tracked through interactions such as occlusion.
Learning and recognizing human dynamics in video sequences
  • C. Bregler
  • Computer Science
    Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition
  • 1997
A probabilistic decomposition of human dynamics at multiple abstractions is described, and how to propagate hypotheses across space, time, and abstraction levels is shown.
Efficient and robust vehicle localization
A novel algorithm for efficient and robust pose determination of vehicles in traffic scenes from single monocular intensity images using calibrated cameras is proposed, avoiding the usual shortcoming of relatively high computational cost of traditional 3D-model based approaches.
Non-linear adaptive fault detection filter
A novel non-linear adaptive fault detection filter (NAFDF) is proposed. It can be used to detect on-line and isolate the faults of a class of non-linear systems arising from accidental jumps of the