Title
Growing competitive network for tracking objects in video sequences
Abstract
The aim of this paper is to present the use of Growing Competitive Neural Networks as a precise method to track moving objects for video-surveillance. The number of neurons in this neural model can be automatically increased or decreased in order to get a one-to-one association between objects currently in the scene and neurons. This association is kept in each frame, what constitutes the foundations of this tracking system. Experiments show that our method is capable to accurately track objects in real-world video sequences.
Year
DOI
Venue
2009
10.1007/978-3-642-04921-7_12
ICANNGA
Keywords
Field
DocType
precise method,real-world video sequence,competitive network,one-to-one association,tracking system,neural model,competitive neural networks,neural network
Computer vision,Computer graphics (images),Computer science,Tracking system,Video tracking,Artificial intelligence,Artificial neural network
Conference
Volume
ISSN
ISBN
5495.0
0302-9743
3-642-04920-6
Citations 
PageRank 
References 
1
0.34
14
Authors
4
Name
Order
Citations
PageRank
J. M. Ortiz-de-Lazcano-Lobato191.91
Rafael M. Luque2477.38
D. López-Rodríguez371.81
E. J. Palomo4384.62