Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Background Modeling for Segmentation of Video-Rate Stereo Sequences
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
W4: Who? When? Where? What? A Real Time System for Detecting and Tracking People
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
A Hierarchical Approach to Robust Background Subtraction using Color and Gradient Information
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
A Real-Time System for Monitoring of Cyclists and Pedestrians
VS '99 Proceedings of the Second IEEE Workshop on Visual Surveillance
Hydra: Multiple People Detection and Tracking Using Silhouettes
VS '99 Proceedings of the Second IEEE Workshop on Visual Surveillance
Foreground Object Detection in Changing Background Based on Color Co-Occurrence Statistics
WACV '02 Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision
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We present an implementation for fast detection of moving objects in real time monitoring applications. We apply a common technique known as background subtraction for this purpose. Background subtraction can be defined as the process of extracting the regions of interest from a given image. Over the last few decades or so, many background subtraction algorithms have appeared. They have been tailored for various applications. In this paper, we intend to propose an alternative implementation suitable for real-time monitoring applications. We do this by reducing the complexity of our mathematical model used for background modeling. We find that this tecnique might be an interesting alternative for many applications.