| EID=330566 | EID:330566,
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LastModified:2017年8月18日(金) 17:51:07,
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Censor:承認済,
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| ○種別 (必須): | □ | 学術論文 (審査論文)
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| ○言語 (必須): | □ | 中国語
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| ○招待 (推奨): |
| ○審査 (推奨): | □ | Peer Review
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| ○カテゴリ (推奨): | □ | 研究
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| ○共著種別 (推奨): | □ | 国際共著 (徳島大学内研究者と国外研究機関所属研究者との共同研究)
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| ○学究種別 (推奨): |
| ○組織 (推奨): | 1. | 徳島大学.大学院ソシオテクノサイエンス研究部.情報ソリューション部門 (2006年4月1日〜)
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| ○著者 (必須): | 1. | (英) Wang, Xiaohua (日) (読)
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| 2. | (英) Li, Ruijing (日) (読)
| ○役割 (任意): | □ | (英) (日) 共著者として研究総括をおこなった．
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| 3. | (英) Hu, Min (日) (読)
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| 4. | 任 福継 (->個人[中川 福継])
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| ○題名 (必須): | □ | (英) Occluded facial expression recognition based on the fusion of local features (日)
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| ○要約 (任意): | □ | (英) To reduce the effect of partial occlusion in facial expression recognition, this paper proposes a new method of facial expression recognition based on local feature fusion. Method First, the normalized images are processed by the Gaussian filter to reduce the effect of noise. According to their different contributions in facial expression recognition, all the images are then divided into two main parts: near the eye and near the mouth. To analyze considerable structure detail, these two parts are further divided into several non-overlapping blocks. The following two patterns are used to extract the features of each sub block: the difference center-symmetric local binary pattern, which is the change of center-symmetric local binary pattern; and the gradient center-symmetric local directional pattern, which is the change of difference local directional pattern. The features are marked as two binary sequences, which are then cascaded to obtain the characteristic histogram of the sub block. The final histogram of the image is obtained by cascading the histogram of each sub block. Finally, the nearest neighbor method is used for classification. Chi-square distance is used to calculate the distance among the characteristic histograms of the testing and training images. Considering the difference of the amount of information contained in each sub block and to reduce the effect of occlusion further, information entropy is used to weigh chi-square distance adaptively. Result Three cross experiments are conducted on JAFFE and CK databases. The average recognition accuracies in random occlusion, mouth occlusion, and eye occlusion cases are 92.86%, 94.76%, and 86.19% on JAFFE database, and are 99%, 98.67%, and 99% on CK database. Conclusion In the aspect of feature extraction, our method describes the image from two aspects: one is the difference of the pixel values in the gradient direction, and the other is the difference of the edge response values between gradient directions. Accordingly, the image can be fully described. In the aspect of occlusion, image segmentation and information entropy are used to weigh chi-square distance adaptively. Thus, our method can effectively reduce the effect of occlusion. Under the same experimental conditions, experimental results show the effectiveness and superiority of the proposed method to other classical local feature extraction and occlusion handling methods. (日)
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| ○キーワード (推奨): |
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| ○誌名 (必須): | □ | (英) Journal of Image and Graphics (日) (読)
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| ○巻 (必須): | □ | 21
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| ○号 (必須): | □ | 11
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| ○頁 (必須): | □ | 1473 1482
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| ○年月日 (必須): | □ | 西暦 2016年 11月 初日 (平成 28年 11月 初日)
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| ○DOI (任意): | □ | 10.11834/jig.20161107 (→Scopusで検索)
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