順伝播型ニューラルネットワークを用いた口唇形状自動抽出法

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2018/12/01

タイトル(英語): Automatic Extraction of Lip Shape Using Feedforward Neural Network

著者名: 中村　悦郎（秋田大学大学院理工学研究科），髙橋　毅（秋田大学大学院理工学研究科），景山　陽一（秋田大学大学院理工学研究科），石井　雅樹（秋田県立大学 システム科学技術学部），西田　眞（放送大学秋田学習センター）

著者名(英語): Etsuro Nakamura (Graduate School of Engineering Science, Akita University), Tsuyoshi Takahashi (Graduate School of Engineering Science, Akita University), Yoichi Kageyama (Graduate School of Engineering Science, Akita University), Masaki Ishii (Akita Pref

キーワード: 口唇，口裂，顔画像，順伝播型ニューラルネットワーク，機械学習　　lip，rima oris，facial image，feedforward neural network，machine learning

要約(英語): Lip motion features such as changes in the lip width and length provide important information for analyzing psychology and physical conditions. Furthermore, extracting lip motions from facial images of users has some advantages that are "needless of special equipment" and "possible of non-contact measuring". Our previous studies revealed that lip motions relate to mental state. Therefore, it is important to develop a method for extracting the lip shape from facial image data. However, the conventional method failed to extract lips due to individual differences of each subject and influences of the shadows on the periphery of lips. Lip extraction methods based on feature points need to use a lot of learning data. In this paper, we propose a novel lip extraction method using feedforward neural network (FFNN), which is one of machine learning methods. The proposed method is able to learn the features of lips using only one image, and its accuracy is same or higher than that of the conventional method and feature-point-based methods.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.138 No.12 （2018） 特集：電気・電子・情報関係学会東海支部連合大会

本誌掲載ページ: 1604-1612 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/138/12/138_1604/_article/-char/ja/