查詢結果分析
來源資料
相關文獻
- A Comparison of Methods for Face Recognition Systems
- The Global Minimum of Scalar Quantization Errors by Discrete Wavelet Transforms in Image Compression
- 影像資料庫在人臉辨識上的應用--前科犯資料庫
- 強健型離散小波轉換於水下響聲之偵測
- 植基於EZW之程式實際設計與執行
- 一個簡單而有效的人臉自動辨識系統之簡介
- Time Series Prediction using Neural Networks with Correlation-Dimension-Based Feature Selection
- 以支持向量機發展之快速人臉偵測系統
- 一種以降低辨識錯誤為基礎的最佳化輻射型基底函數建構法
- 最佳化輻射型基底函數人臉辨識法
頁籤選單縮合
題 名 | A Comparison of Methods for Face Recognition Systems=臉部辨識系統方法比較 |
---|---|
作 者 | 郭振輝; 賴岦俊; | 書刊名 | 工程應用技術學刊 |
卷 期 | 1:1 2012.02[民101.02] |
頁 次 | 頁149-171 |
分類號 | 312.13 |
關鍵詞 | 人臉辨識; 支持向量機; 特徵選取; 隱馬可夫模型; 離散餘旋轉換; 離散小波轉換; Face recognition; Support vector machine; Feature selection; Hidden Markov model; Discrete cosine transform; Discrete wavelet transform; |
語 文 | 英文(English) |
中文摘要 | 在本文中提出DCT與DWT兩種特徵選取方法之比較、SVM與HMM分類器方法之比較、兩種掃瞄方式之效能比較:上到下掃瞄與光柵掃瞄。DCT與DWT被用在頻域分析主要在減少特徵數量,然而實驗證明應用在人臉辨識兩者效果是一樣。SVM原本設計在線性二類別之分類,在本實驗上選用一對一方法作為多類別分類器,實驗證明它在資料庫較大時,比一對多方法之多類別分類器效果要好。HMM成功的應用在語音辨識,比較SVM與HMM分類器在人臉辨識之差異性為本篇文章之主軸,實驗利用ORL人臉資料庫,比較上述方法之差別。 |
英文摘要 | In this paper, we propose a comparison of DCT and DWT methods for feature selection, also comparison of SVM and HMM methods for facial classifiers. We used two scan methods, top-bottom and raster scan, on purpose for data scan and then to compare the performance of two scan method. The DCT and DWT are used to frequency domain analysis to reduce the feature dimension. Nevertheless, we prove that they are the same result if apply our extract feature method. SVM was originally designed for linear binary classification. Our experiments use one-against-one method for multi-class classification because it's more suitable for practical use than the method of one-against-all. HMM has been applied with success in speech recognition. This paper reports on a comparison of the two classifiers in facial recognition. We have tested two classifiers on the ORL facial database. |
本系統中英文摘要資訊取自各篇刊載內容。