Shape Analysis and Classification: Theory and Practice
Shape Analysis and Classification: Theory and Practice
Pattern Analysis & Applications
A PCA-Based Vehicle Classification Framework
ICDEW '06 Proceedings of the 22nd International Conference on Data Engineering Workshops
Improved Vehicle Classification in Long Traffic Video by Cooperating Tracker and Classifier Modules
AVSS '06 Proceedings of the IEEE International Conference on Video and Signal Based Surveillance
Initialization of Model-Based Vehicle Tracking in Video Sequences of Inner-City Intersections
International Journal of Computer Vision
Urban Vehicle Tracking Using a Combined 3D Model Detector and Classifier
KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part I
Comparison of stochastic filtering methods for 3D tracking
Pattern Recognition
Vehicle classification from traffic surveillance videos at a finer granularity
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
Depth Map and 3D Imaging Applications: Algorithms and Technologies
Depth Map and 3D Imaging Applications: Algorithms and Technologies
Detection and classification of vehicles
IEEE Transactions on Intelligent Transportation Systems
Automatic traffic surveillance system for vehicle tracking and classification
IEEE Transactions on Intelligent Transportation Systems
| Hi-index | 0.00 |
In this paper, the authors propose a model for classification of moving vehicles in traffic videos. A corner-based tracking method is presented to track and detect moving vehicles. The authors propose to overlap the boundary curves of each of the detected moving vehicles while tracking in a sequence of frames to reconstruct a complete boundary shape of the vehicle. The reconstructed boundary shape is normalized and then shape features are extracted. Vehicles are categorized into 4 different types of vehicle classes using KNN rule, the weighted KNN, PNN, and SVM classifiers. Experiments are conducted on traffic video sequences captured in an uncontrolled environment during daytime.