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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/68953

    Title: 基於聯合字典學習與辨識器的局部保留 K-SVD 於物件辨識之研究;A Study on Locality Preserving K-SVD via Joint Dictionary and Classifier Learning for Object Recognition
    Authors: 趙家豪;Zhao,Jia-hao
    Contributors: 資訊工程學系
    Keywords: K-SVD;DK-SVD;聯合字典學習;局部保留;物件辨識;K-SVD;DK-SVD;Joint Dictionary Learning;Locality Preserving;Object Recognition
    Date: 2015-08-24
    Issue Date: 2015-09-23 14:47:19 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 電腦視覺是一門研究如何令機器理解圖像的科學,隨著現在電腦速度的改進,處理圖像這種大規模資料的應用漸漸地扮演了舉足輕重的腳色,而物件辨識(Object Recognition),就是其中一種相當熱門的技術,為了達到精準辨識的目的,從傳統的支持向量機(SVM)、稀疏表示分類器(SRC)以及DK-SVD(Discriminative K-SVD),皆能獲得一定的效果。
    ;Computer vision is a field that understanding images. Along with advances in computer performance, processing large-scale data becomes more common than before. Object Recognition is one of the popular computer vision technology. In order to enhance the recognition performance, we can use the traditional SVM, SRC and DK-SVD.
    In this paper, we present locality preserving K-SVD based on DK-KSVD. Adding the locality preserving term into the objective function to preserve the neighborhood structure of the data set. The locality preserving term can be used as a new feature. We can gain additional locality information for new input signals. We also apply kernel method on the dictionary learning which efficiently strengthen the reconstructive and discriminative ability.
    Experiments on Caltech101 and 15Scene databases indicate that the proposed method achieve good recognition performance.
    Appears in Collections:[資訊工程研究所] 博碩士論文

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