Non-parametric Model for Background Subtraction
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Summary
A novel non-parametric background model that can handle situations where the background of the scene is cluttered and not completely static but contains small motions such as tree branches and bushes is presented.
- Published
- 2000-06-26
- Cited by
- 2,515
- References
- 10
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:15761330
References
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- and as an in
Cited by
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- Combining Motion Detection and Hierarchical Particle Filter Tracking in a Multi-player Sports Environment.
- Labeling hypergraph-structured data using markov network
- Robust Bilayer Segmentation and Motion/Depth Estimation with a Handheld Camera
- Visual Traffic Noise Monitoring in Urban Areas
- Enhancing the Potential of the Conventional Gaussian Mixture Model for Segmentation: from Images to Videos
- Scene Understanding: perception, multi-sensor fusion, spatio-temporal reasoning and activity recognition. (Interprétation de Scènes : perception, fusion multi-capteurs, raisonnement spatio-temporel et reconnaissance d'activités)
- On-board three-dimensional object tracking: Software and hardware solutions
- Improved Cut-Based Foreground Identification
- Multiple Cue Data Fusion using Markov Random Fields for Motion Detection
- Light and Water Drops
- Real-time Tracking of Participants in Meeting Video
- Handling Occlusions in Monocular Surveillance Systems
- Robust Techniques for Visual Surveillance
- An energy-based background modelling algorithm for motion detection
- Background Subtraction with Adaptive Spatio-Temporal Neighborhood Analysis
- Scene Analysis under Variable Illumination using Gradient Domain Methods
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