کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
558347 1451725 2016 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Adaptive linear discriminant regression classification for face recognition
ترجمه فارسی عنوان
طبقه بندی رگرسيون خطي تقسيم كننده براي تشخيص چهره
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
چکیده انگلیسی

Linear discriminant regression classification (LDRC) was presented recently in order to boost the effectiveness of linear regression classification (LRC). LDRC aims to find a subspace for LRC where LRC can achieve a high discrimination for classification. As a discriminant analysis algorithm, however, LDRC considers an equal importance of each training sample and ignores the different contributions of these samples to learn the discriminative feature subspace for classification. Motivated by the fact that some training samples are more effectual in learning the low-dimensional feature space than other samples, in this paper, we propose an adaptive linear discriminant regression classification (ALDRC) algorithm by taking special consideration of different contributions of the training samples. Specifically, ALDRC makes use of different weights to characterize the different contributions of the training samples and utilizes such weighting information to calculate the between-class and the within-class reconstruction errors, and then ALDRC seeks to find an optimal projection matrix that can maximize the ratio of the between-class reconstruction error over the within-class reconstruction error. Extensive experiments carried out on the AR, FERET and ORL face databases demonstrate the effectiveness of the proposed method.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Digital Signal Processing - Volume 55, August 2016, Pages 78–84
نویسندگان
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