Paper Info
Title
The PCA-Based long distance face recognition using multiple distance training images for intelligent surveillance system
Abstract
In this paper, PCA-based long distance face recognition algorithm applicable to the environment of intelligent video surveillance system is proposed. While the existing face recognition algorithm uses the short distance images for training images, the proposed algorithm uses face images by distance extracted from 1m to 5m for training images. Face images by distance, which are used for training images and test images, are normalized through bilinear interpolation. The proposed algorithm has improved face recognition performance by 4.8% in short distance and 16.5% in long distance so it is applicable to the intelligent video surveillance system.
Year
DOI
Venue
2013
10.1007/978-3-642-36818-9_62
ICT-EurAsia
Keywords
Field
DocType
face recognition performance,face image,multiple distance training image,pca-based long distance face,short distance image,intelligent surveillance system,training image,long distance,existing face recognition algorithm,short distance,intelligent video surveillance system,proposed algorithm,image interpolation
Facial recognition system,Computer vision,Normalization (statistics),Object-class detection,Pattern recognition,Computer science,Artificial intelligence,Image scaling,Bilinear interpolation
Conference
Citations 
PageRank 
References 
0
0.34
4
Authors
2
Name
Order
Citations
PageRank
Hae-Min Moon1377.49
Sung Bum Pan216236.88