{"_buckets": {"deposit": "80fef464-6a1b-4675-9532-f56a791168ea"}, "_deposit": {"id": "21696", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "21696"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00021696"}, "item_10_alternative_title_19": {"attribute_name": "\u305d\u306e\u4ed6\u306e\u8a00\u8a9e\u306e\u30bf\u30a4\u30c8\u30eb", "attribute_value_mlt": [{"subitem_alternative_title": "A study on facial pose transformation based on learning-based local image transformation"}]}, "item_10_biblio_info_6": {"attribute_name": "\u66f8\u8a8c\u60c5\u5831", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2011-03-03", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "467", "bibliographicPageEnd": "150", "bibliographicPageStart": "145", "bibliographicVolumeNumber": "110", "bibliographic_titles": [{"bibliographic_title": "\u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\u6280\u8853\u7814\u7a76\u5831\u544a. 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However, the facial pose of a person in surveillance camera images often differs from the facial pose in an person identification database. Therefore, it is difficult to identify a person in the image. In this report, we propose a method for facial poses transformation based on a learning-based local image transformation. It tackles face recognition across pose by virtually transforming a facial pose to the pose in the person identification database. The proposed method transforms facial poses using a face image dataset which consists of face images of a large number of individuals with various poses. I performs a patch-wise transformation, which transforms a partial image (patch) in a face at each location on the face. Also, it is necessary to find correspondences of patches between different poses and individuals so that the same part should be contained in the patches for achieving accurate pose transformation. A face recognition experiment was conducted with frontal face images transformed by the proposed method. 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