The PCA-Based Long Distance Face Recognition Using Multiple Distance Training Images for Intelligent Surveillance System - Information and Communication Technology
Conference Papers Year : 2013

The PCA-Based Long Distance Face Recognition Using Multiple Distance Training Images for Intelligent Surveillance System

Hae-Min Moon
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  • PersonId : 1003131
Sung Bum Pan
  • Function : Author
  • PersonId : 1003132

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.
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hal-01480214 , version 1 (01-03-2017)

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Hae-Min Moon, Sung Bum Pan. The PCA-Based Long Distance Face Recognition Using Multiple Distance Training Images for Intelligent Surveillance System. 1st International Conference on Information and Communication Technology (ICT-EurAsia), Mar 2013, Yogyakarta, Indonesia. pp.534-539, ⟨10.1007/978-3-642-36818-9_62⟩. ⟨hal-01480214⟩
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