English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 55184/89457 (62%)
造訪人次 : 10668889      線上人數 : 74
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/113055

    題名: A new approach for face hallucination based on a two-dimensional direct combined model
    作者: Tu, Ching-Ting;Ho, Mei-Chi;Lin, Meng-Ying
    關鍵詞: Principal Component Analysis (PCA)Canonical Correlation Analysis (CCA)EigenfacesFacial hallucination
    日期: 2017-02
    上傳時間: 2018-03-31 12:10:25 (UTC+8)
    摘要: This study develops an example-based face hallucination system based on a novel two-dimensional direct combined model (2DDCM) approach. The 2DDCM model combines the low-resolution and high-resolution pairwise images in the training set in a combined (or concatenated) matrix form in order to better preserve the correlation between the two images during the system learning process. Notably, the images processed by the 2DDCM model have the form of two-dimensional (2D) matrices rather than one-dimensional (1D) vectors, and hence the facial geometry features in the vertical and horizontal directions can be more reliably extracted. The proposed hallucination system comprises two 2DDCM-based modules, namely a global module for global facial structure reconstruction and a local module for facial texture detail compensation. In implementing the local module, a 2DDCM-based bi-directional transformation method is adopted to identify the detailed facial textures which are lost in the global synthesis process. The experimental results show that the synthesized results obtained using the proposed 2DDCM framework are in good quantitative agreement with the ground-truth images. Moreover, the proposed framework demonstrates the ability to synthesize high-resolution facial images given only a small number of training pairs, even when the facial features, alignment and appearance of the testing image differ from those of the original training set. Finally, the 2DDCM representation ensures that the synthesized results better preserve the subject-specific characteristics of the input facial image, and therefore improves the performance of downstream applications such as automatic face recognition.
    關聯: Pattern Recognition 62, pp. 1-20
    DOI: 10.1016/j.patcog.2016.07.020
    顯示於類別:[資訊工程學系暨研究所] 期刊論文


    檔案 描述 大小格式瀏覽次數
    A new approach for face hallucination based on a two-dimensional direct combined model.pdf5660KbAdobe PDF0檢視/開啟



    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋