A Self-organizing Neural System for Background and Foreground Modeling
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Multivalued Background/Foreground Separation for Moving Object Detection
WILF '09 Proceedings of the 8th International Workshop on Fuzzy Logic and Applications
3D Neural Model-Based Stopped Object Detection
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
A 3D Neural Model for Video Analysis
Proceedings of the 2009 conference on Neural Nets WIRN09: Proceedings of the 19th Italian Workshop on Neural Nets, Vietri sul Mare, Salerno, Italy, May 28--30 2009
Simplified SOM-neural model for video segmentation of moving objects
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Advanced motion detection for intelligent video surveillance systems
Proceedings of the 2010 ACM Symposium on Applied Computing
Adaptive shadow estimator for removing shadow of moving object
Computer Vision and Image Understanding
Moving target tracking and measurement with a binocular vision system
International Journal of Computer Applications in Technology
Survey on contemporary remote surveillance systems for public safety
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
An algorithm for recovering camouflage errors on moving people
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
An experimental evaluation of foreground detection algorithms in real scenes
EURASIP Journal on Advances in Signal Processing - Special issue on video analysis for human behavior understanding
Journal on Image and Video Processing - Special issue on advanced video-based surveillance
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Real-time stopped object detection by neural dual background modeling
Euro-Par 2010 Proceedings of the 2010 conference on Parallel processing
Background extraction using improved mode algorithm for visual surveillance applications
International Journal of Computational Science and Engineering
Shadow detection: A survey and comparative evaluation of recent methods
Pattern Recognition
An efficient continuous tracking system in real-time surveillance application
Journal of Network and Computer Applications
Background modeling by subspace learning on spatio-temporal patches
Pattern Recognition Letters
Background subtraction based on phase feature and distance transform
Pattern Recognition Letters
Motion detection with pyramid structure of background model for intelligent surveillance systems
Engineering Applications of Artificial Intelligence
Robust detection of moving objects in video sequences through rough set theory framework
Image and Vision Computing
Hierarchical framework for robust and fast multiple-target tracking in surveillance scenarios
Expert Systems with Applications: An International Journal
Block-Sparse RPCA for consistent foreground detection
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Background subtraction with dirichlet processes
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Euler Principal Component Analysis
International Journal of Computer Vision
A new framework for background subtraction using multiple cues
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Steering kernel-based video moving objects detection with local background texture dictionaries
Computers and Electrical Engineering
Granulation, rough entropy and spatiotemporal moving object detection
Applied Soft Computing
Human activity modeling by spatio temporal textural appearance
Pattern Recognition Letters
Finite asymmetric generalized Gaussian mixture models learning for infrared object detection
Computer Vision and Image Understanding
Pose Depth Volume extraction from RGB-D streams for frontal gait recognition
Journal of Visual Communication and Image Representation
Background foreground segmentation with RGB-D Kinect data: An efficient combination of classifiers
Journal of Visual Communication and Image Representation
Fast background subtraction using static and dynamic gates
Artificial Intelligence Review
Unsupervised Tracking, Roughness and Quantitative Indices
Fundamenta Informaticae - Cognitive Informatics and Computational Intelligence: Theory and Applications
Real-time background modeling based on a multi-level texture description
Information Sciences: an International Journal
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Detection of moving objects in video streams is the first relevant step of information extraction in many computer vision applications. Aside from the intrinsic usefulness of being able to segment video streams into moving and background components, detecting moving objects provides a focus of attention for recognition, classification, and activity analysis, making these later steps more efficient. We propose an approach based on self organization through artificial neural networks, widely applied in human image processing systems and more generally in cognitive science. The proposed approach can handle scenes containing moving backgrounds, gradual illumination variations and camouflage, has no bootstrapping limitations, can include into the background model shadows cast by moving objects, and achieves robust detection for different types of videos taken with stationary cameras. We compare our method with other modeling techniques and report experimental results, both in terms of detection accuracy and in terms of processing speed, for color video sequences that represent typical situations critical for video surveillance systems.