【正文】 面部表情在人們交流 中有著重要的作用 ,它不僅可以準(zhǔn)確表達(dá)人類的思想感情 ,而且也可以通過面部 表情來了解對(duì)方的態(tài)度和內(nèi)心世界 ,心理學(xué)家曾給出一個(gè)公式 :7%的言詞+38% [1] 的聲音 +55%的面部表情傳遞人類的感情表達(dá) ,從公式中可以清楚的看到人臉 表情與情感表達(dá)的關(guān)系之密切。近 年來 ,它的實(shí)際應(yīng)用領(lǐng)域也從最初的光學(xué)字符識(shí)別 ,發(fā)展到現(xiàn)在的生物身份認(rèn)證、 DNA 序列分析、化學(xué)氣味識(shí)別、藥物分子識(shí)別、醫(yī)學(xué)病灶識(shí)別、圖像理 解、人 臉識(shí)別、表情識(shí)別、手勢(shì)識(shí)別、語音識(shí)別、信息檢索、數(shù)據(jù)挖掘和信號(hào)處理等領(lǐng) 域。 √ 不保密□。本人授權(quán)中南民族大學(xué)可以將本學(xué)位論文的全部或部分內(nèi) 容編入有關(guān)數(shù)據(jù)庫進(jìn)行檢索 ,可以采用影印、縮印或掃描等復(fù)制手段保存 和匯編本學(xué)位論文。本人完全意識(shí)到本聲明的 法律后果由本人承擔(dān)。除了文中特別加以標(biāo)注引用的內(nèi)容外 ,本論文不包含任 何其他個(gè)人或集體已經(jīng)發(fā)表或撰寫的成果作品。 Adaboost。決策樹分類器 I 中南民族大學(xué)碩士學(xué)位論文 Abstract Facial expression is a basic form of human expression of emotions, it plays an important role in the people’s exchange, not only can express human thoughts and feelings accurately, but also through facial expressions to understand each others’attitudes and inner world. Automatic facial recognition is premise of understanding the human emotions for puters, and it has unlimited potential in real life, such as humanputer interaction, affective puting, psychology, clinical medicine. Because of this special role, people do much more work in this areaThe past 20 years, facial expression recognition method has been made very significant progress. However, due to facail expression recognition involves image processing, psychology, puter vision, artificial intelligence and other subjects, Because of this plexity and particularity, there are a lot of problems need to solveThis paper focuses on the accuracy of facial recognition. to carry out the exploration of key , this paper’s main contents include the following aspects: First of all, on the Adaboost algorithm, the main study is how to solve multiclassification problem, weak classifiers would be constructed by Adaboost algorithm to generate a strong classifier. To solve the multiclass classification problem, we designed classifier by onetoone mode, so the number of strong classifiers of Adaboost was k(k1)/2 k,number of categoriesSecondly, on analysis and parison of a variety of classificaion, the main work is on the nearest neighbor method, and the decision tree, by analyzing the principle of the two algorithms, and paring them based on the characteristics of the different classifiers. For facial expression recognition problems, this two classifiers are used as the weak classifers in the Adaboost algorithm, and pares their performance Then study the expression of feature extraction algorithms, the principle of Gabor filters is conducted indepth analysis and research, analyzing and paring the parameters of Gabor filter, in order to gain the most suitable parameters of the Gabor filtersFinally, we bined the Adaboost algorithm, decision tree classifier, Gabor features to study facial expression recognition, and used the JAFFE expression database and the Yale face image database to test. In the last, not only summarizes this paper’s work, but also clearly defined the direction an d goals of future workThe proposed facial expression recognition based on Gabor feature and Adaboost can solve multiclass classificaion problems effectively. The results also show that this algorithm can improve the accuracy of identification and obtain better recognition resultsKey words: Facail expression recognitionFER。Gabor 特征 。 本論文所提出的基于 Gabor 特征和 Adaboost 算法的人臉表情識(shí)別方法 ,可 以有效的解決多類分類的問題 ,實(shí)驗(yàn)結(jié)果也表明了該算法可以提高識(shí)別的準(zhǔn)確 率 ,獲得較好的識(shí)別效果。 最后將 Adaboost 算法 ,決策樹分類器 ,Gabor 特征結(jié)合 ,進(jìn)行人臉表情識(shí)別 研究 ,并使用 JAFFE 人臉表情數(shù)據(jù)庫 ,以及 Yale 數(shù)據(jù)庫中的表情圖像進(jìn)行測(cè)試。針對(duì)人臉表情識(shí)別問題 ,分別使用這兩種分 類器作為 Adaboost 算 法的弱分類器進(jìn)行識(shí)別 ,比較了它們的性能。 其次 ,分析和比較了多種分類器。主要研究了如何利用 Adaboost 算法進(jìn) 行多類分類的問題。但是由于人臉表情識(shí)別涉 及圖像處理、心理學(xué)、計(jì)算機(jī)視覺、人工智能等多個(gè)學(xué)科交叉 ,正是由于這種多 學(xué)科交叉的復(fù)雜性和特殊性 ,使得表情識(shí)別比較困難 ,當(dāng)前人們?nèi)悦媾R著許多亟 待解決的問題。正是由于這種特殊的作用 ,所以人們對(duì)表情自動(dòng)識(shí)別進(jìn)行了大量的研究?；?Gabor 特征和 Adaboost算法的人臉表情識(shí)別研究 畢業(yè)論文 中南民族大學(xué) 碩士學(xué)位論文 基于 Gabor 特征和 Adaboost 算法的人臉表情識(shí)別研究 姓名 :劉 ? 申請(qǐng)學(xué)位級(jí)別 :碩士 專業(yè) :生物醫(yī)學(xué)工程 指導(dǎo)教師 :高智勇 20200524 中南民族大學(xué)碩士學(xué)位論文 摘 要 表情是人類表達(dá)情緒的基本方式之一 ,面部表情在人們交流中有著重要的作 用 ,它不僅可以準(zhǔn)確表達(dá)人類的思想感情 ,而且也可以通過面部表情來了解對(duì)方 的態(tài)度和內(nèi)心世界。自動(dòng)表情識(shí)別是計(jì) 算機(jī)理解人類情感的前提 ,在現(xiàn)實(shí)生活中 有著無限的潛力 ,例如人機(jī)交互、情感計(jì)算、心理學(xué)研究、謊言辨別 ,臨床醫(yī)