Foreground Detection by Competitive Learning for Varying Input Distributions.
Ezequiel López-RubioMiguel A. Molina-CabelloRafael Marcos Luque BaenaEnrique DomínguezPublished in: Int. J. Neural Syst. (2018)
Keyphrases
- competitive learning
- foreground detection
- neural network
- self organizing maps
- information theoretic
- background subtraction
- human detection
- background modeling
- data clustering
- video surveillance
- unsupervised learning
- foreground objects
- probability distribution
- dynamic background
- object detection
- k means
- moving objects
- input data
- pairwise
- input image
- image sequences