Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual Attention Mechanisms
Detected motion classification with a double-background and a neighborhood-based difference
Pattern Recognition Letters
Robust abandoned object detection using dual foregrounds
EURASIP Journal on Advances in Signal Processing
Robust Foreground Detection In Video Using Pixel Layers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stationary target detection using the objectvideo surveillance system
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
Stationary objects in multiple object tracking
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
A DSP-based system for the detection of vehicles parked in prohibited areas
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
2007 IEEE Conference on advanced video and signal based surveillance
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
Real-time foreground-background segmentation using codebook model
Real-Time Imaging
Image change detection algorithms: a systematic survey
IEEE Transactions on Image Processing
A Scale-Based Connected Coherence Tree Algorithm for Image Segmentation
IEEE Transactions on Image Processing
A Self-Organizing Approach to Background Subtraction for Visual Surveillance Applications
IEEE Transactions on Image Processing
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In this paper we propose a system that is able to distinguish moving and stopped objects in digital image sequences taken from stationary cameras. Our approach is based on self organization through artificial neural networks to construct a model of the scene background and a model of the scene foreground that can handle scenes containing moving backgrounds or gradual illumination variations, helping in distinguishing between moving and stopped foreground regions, leading to an initial segmentation of scene objects. Experimental results are presented for video sequences that represent typical situations critical for detecting vehicles stopped in no parking areas and compared with those obtained by other existing approaches.