Visual Language Identification from Facial Landmarks
Visual Language Identification from Facial Landmarks
复制标题
从面部标志进行视觉语言识别
DOI：
10.1007/978-3-319-59129-2_33
复制
发表时间：
2017
期刊：
影响因子：
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通讯作者：
Jiri Matas
中科院分区：
文献类型：
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作者：
Radim Spetlik;Jan Cech;Vojtech Franc;Jiri Matas
研究了视觉语言自动识别（VLID）问题，即在不使用音频信息的情况下，使用视觉信息来识别被说话人的语言。该方法利用视频中自动检测到的面部特征。提出了一个凸优化问题，以联合找到判别表示（唇形集上的软直方图）和分类器。对从youtube.com收集的644个视频组成的数据集进行了10倍交叉验证，结果在英语和法语的两两区分中准确率为73%（50%为机会）。一项使用了10个视频的研究表明，所提出的方法在区分语言方面比普通人表现得更好。
The automatic Visual Language IDentification (VLID), i.e. a problem of using visual information to identify the language being spoken, using no audio information, is studied. The proposed method employs facial landmarks automatically detected in a video. A convex optimisation problem to find jointly both the discriminative representation (a soft-histogram over a set of lip shapes) and the classifier is formulated. A 10-fold cross-validation is performed on dataset consisting of 644 videos collected from youtube.com resulting in accuracy 73% in a pairwise discrimination between English and French (50% for a chance). A study, in which 10 videos were used, suggests that the proposed method performs better than average human in discriminating between the languages.