利用非線性判別分析與位階排名的年齡估計研究

A Ranking Approach on Age Estimation Via Constrained Kernel Discriminant Analysis

羅凱文(Kai-Wen Luo)

指導教授 ： 許秋婷

國立清華大學/電機資訊學院/資訊工程學系/碩士(2012年)

https://doi.org/10.6843/NTHU.2012.00485

摘要

在本篇論文中，我們提出了一個以限制條件的非線性判別分析加上位階概念的方法來實現年齡估計。不同於以往的方法，我們的演算法是根據一對人臉影像中具有順序的資訊加以處理：我們使用了兩張不同年紀的人臉圖案的差值來當做我們使用的特徵，而非原始的整張影像。我們所提出的限制條件的非線性判別分析能經由對一對對人臉影像差值的分類工作，求得原始單張影像的位階(順序)值. 我們接著就用求得的位階值來做年齡估計。此外，為了達到正確的年齡估計，我們所加上的限制是針對同年紀的單張影像，讓它們在投影之後位階值能夠靠近。在本篇論文中，我們會說明一對人臉影像的差值可被當作具有鑑別力的特徵，及我們加上的限制可有效地降低誤差。從實驗結果來看，我們的方法也與現有的方法不分軒輊。

關鍵字

年齡估計 ； 位階 ； 非線性判別分析

並列摘要

In this thesis, we propose a constrained kernel discriminant analysis (CKDA) to realize age estimation via the ranking concept. Unlike the previous work, the design of our algorithm is based on the relative order information among the pairwise facial images. In other words, we propose to utilize the difference of the data pairs as the feature rather than the original image samples. We first extract the ranking relation via binary classification on pairwise data and then conduct CKDA to compute the ranking (ordered) value of each sample via binary classifier. We next use this ranking value to do the age estimation. In addition, we further include a constraint on original samples according to their age labels to improve the estimation accuracy. In this paper, we show that the differences of image pairs can be a discriminant feature for age estimation, and our constraint also effectively decreases the error. Experimental result shows that the performance of our method is comparable to other existing works.

並列關鍵字

age esitmation ； ranking ； kernel discriminant analysis ； pairwise

參考文獻

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” International Conference on Pattern Recognition , ICPR 2010

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