以AdaBoost 演算法為基礎的性別辨識(An Adaboost-Based Gender Recognition)

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Title:	以AdaBoost 演算法為基礎的性別辨識(An Adaboost-Based Gender Recognition)
Authors:	黃雅軒 huang, yea-shuan
Contributors:	資訊工程學系 Computer Science & Information Engineering
Keywords:	Adaboost;LBP;SVM;Facial expression recognition;Feature reduction
Date:	2011
Issue Date:	2014-06-27 01:46:48 (UTC+8)
Abstract:	性別辨識在近年來電腦視覺的領域當中，是一個非常重要的議題，其應用面非常廣泛，像是監視系統和針對性別來進行服務或統計之廣告看板等等。若是能在日常生活中確實應用此技術，生活將會變得更加有趣和方便。因此我們針對這項議題，提出了一套新的人臉性別辨識方法：先由Adaboost演算法偵測出大略的人臉位置、眼珠點位置和嘴角位置等資訊後，再根據眼珠點和嘴角位置將人臉影像自整張影像中擷取出來，然後藉由雙眼珠點位置進行人臉影像的轉正和大小正規化運算；接著以本論文所提出的Boosted-LBP演算法，來抽取臉部影像中具有高性別 In recent years, gender recognition has become a very important subject in the computer vision society, which has many applications, such as surveillance systems or advertising billboards. If we can make use of this subject in our daily life, our surround
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