Paper Info
Title
Research on the Design of the Categorization System for Moving Information in Video Stream and Its Implementation
Abstract
The moving objects are what attract most attention in the video surveillance system, and also the key part for study. Currently, the video surveillance system relies much on the subjective initiative of the observers while having the real-time surveillance. In this study, applying the mixture Gaussian model algorithm, the profile image of the moving objects in the picture got from the video surveillance is obtained, and then denoised so as to extract the feature vector of the image. Further, utilizing the already trained neural network, the feature vectors are categorized to elevate the intelligence of the surveillance system and to implement the automatic categorization on the moving objects. It is proved to be effective through the simulation test.
Year
DOI
Venue
2009
10.1109/CSIE.2009.231
CSIE (6)
Keywords
Field
DocType
neural network,trained neural network,profile image,categorization,automatic categorization,categorization system,feature vector,key part,moving objects,mixture gaussian,real-time surveillance,automatic categorization system design,mixture gaussian model algorithm,feature extraction,video stream,gaussian processes,video surveillance system,video streaming,surveillance system,video surveillance,image motion analysis,real time,pixel,computational modeling,artificial neural networks
Computer science,Gaussian process,Artificial intelligence,Artificial neural network,Computer vision,Categorization,Feature vector,Pattern recognition,Feature extraction,Video tracking,Gaussian network model,Pixel,Machine learning
Conference
Volume
ISBN
Citations 
6
978-0-7695-3507-4
0
PageRank 
References 
Authors
0.34
11
6
Name
Order
Citations
PageRank
Haifeng Li1258.83
Zhezhou Yu2225.50
Xubing Ma300.34
Rencai Gao400.68
Li Yang57633.15
Lingjiang Fang600.34