AREA '08 Proceedings of the 1st ACM workshop on Analysis and retrieval of events/actions and workflows in video streams
Coupled multi-object tracking and labeling for vehicle trajectory estimation and matching
Multimedia Tools and Applications
Dynamic background modeling for a safe road design
Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments
Vehicle counting without background modeling
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part I
Object detection with feature stability over scale space
Journal of Visual Communication and Image Representation
Reliable moving vehicle detection based on the filtering of swinging tree leaves and raindrops
Journal of Visual Communication and Image Representation
ANN face detection with skin color distribution rules
Machine Graphics & Vision International Journal
Road Traffic Parameters Estimation by Dynamic Scene Analysis: A Systematic Review
International Journal of Grid and High Performance Computing
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This paper presents an intelligent vehicle counting method based on blob analysis in traffic surveillance. The proposed algorithm is composed of three steps: Processing is done by three main steps: moving object segmentation, blob analysis, and tracking. A vehicle is modeled as a rectangular patch and classified via blob analysis. By analyzing the blob of vehicles, the meaningful features are extracted. Tracking moving targets is achieved by comparing the extracted features and measuring the minimal distance between two temporal images. In addition, the velocity of each vehicle and the vehicle flow through a predefined area can be calculated by analyzing blobs of vehicles. The experimental results show that the proposed system can provide real-time and useful information for traffic surveillance.