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植基於臉部特徵之性別辨識 = Gender Recognition Ba...

國立高雄大學電機工程學系碩士班

植基於臉部特徵之性別辨識 = Gender Recognition Based on Facial Features

Record Type:	Language materials, printed : monographic
Paralel Title:	Gender Recognition Based on Facial Features
Author:	黃彥鈞,
Secondary Intellectual Responsibility:	國立高雄大學
Place of Publication:	[高雄市]
Published:	撰者;
Year of Publication:	2015[民104]
Description:	54面圖，表 : 30公分;
Subject:	支持向量機
Subject:	Local zigzag pattern
Online resource:	http://handle.ncl.edu.tw/11296/ndltd/27016589101113227034
Notes:	104年10月31日公開
Notes:	參考書目：面43-46
Summary:	從給定的影像或影片中判斷一個人的性別是一個有趣的議題。而這是在人機介面、人口統計學、智慧監控系統以及商業分析等許多應用中一個相當重要的前處理步驟。由於人臉包含各種有用的資訊,因此在性別辨識的領域中,已經有許多基於臉部的研究方法被提出。在本篇論文中,我們提出一種新穎的紋理描述子區域鋸齒圖樣,與結合梯度方向圖樣之紋理特徵擷取方法,用於取出臉部的特徵以辨識性別,最後藉由支持向量機分類器進行分類。我們使用FERET、BioID、LFW、CAS-PEAL-R1資料庫中的人臉影像進行相關實驗,實驗結果證實,我們所提出的方法和其他方法相較下具有不錯的辨識效果。 Determining the gender of a person in a given image or video is an interesting problem. It is an important preprocessing step in many applications such as human-computer interaction, demographic data collection, intelligent surveillance, and customer-oriented advertising. Because human faces contain a variety of useful information, a large number of studies based on facial information have been investigated for gender recognition. In this paper, we present a method which combines a novel texture descriptor called local zigzag pattern and the gradient direction pattern for feature extraction to identify the gender from the facial images. The recognition is performed by using a support vector machine. Experimental results on the FERET, BioID, LFW, and CAS-PEAL-R1 databases are provided to illustrate the proposed approach is an effective method, compared to other similar methods.

植基於臉部特徵之性別辨識 = Gender Recognition Based on Facial Features
黃, 彥鈞

植基於臉部特徵之性別辨識 = Gender Recognition Based on Facial Features / 黃彥鈞撰 - [高雄市] : 撰者, 2015[民104]. - 54面 ; 圖，表 ; 30公分.
104年10月31日公開參考書目：面43-46.
支持向量機Local zigzag pattern

植基於臉部特徵之性別辨識 = Gender Recognition Based on Facial Features
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330 $a 從給定的影像或影片中判斷一個人的性別是一個有趣的議題。而這是在人機介面、人口統計學、智慧監控系統以及商業分析等許多應用中一個相當重要的前處理步驟。由於人臉包含各種有用的資訊,因此在性別辨識的領域中,已經有許多基於臉部的研究方法被提出。在本篇論文中,我們提出一種新穎的紋理描述子區域鋸齒圖樣,與結合梯度方向圖樣之紋理特徵擷取方法,用於取出臉部的特徵以辨識性別,最後藉由支持向量機分類器進行分類。我們使用FERET、BioID、LFW、CAS-PEAL-R1資料庫中的人臉影像進行相關實驗,實驗結果證實,我們所提出的方法和其他方法相較下具有不錯的辨識效果。 Determining the gender of a person in a given image or video is an interesting problem. It is an important preprocessing step in many applications such as human-computer interaction, demographic data collection, intelligent surveillance, and customer-oriented advertising. Because human faces contain a variety of useful information, a large number of studies based on facial information have been investigated for gender recognition. In this paper, we present a method which combines a novel texture descriptor called local zigzag pattern and the gradient direction pattern for feature extraction to identify the gender from the facial images. The recognition is performed by using a support vector machine. Experimental results on the FERET, BioID, LFW, and CAS-PEAL-R1 databases are provided to illustrate the proposed approach is an effective method, compared to other similar methods.
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