Using nasal curves matching for expression robust 3D nose recognition
Using nasal curves matching for expression robust 3D nose recognition
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DOI：
10.1109/btas.2013.6712732
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发表时间：
2013-09
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影响因子：
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通讯作者：
Mehryar Emambakhsh;A. Evans;Melvyn L. Smith
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文献类型：
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作者：
Mehryar Emambakhsh;A. Evans;Melvyn L. Smith
在过去十年中，开发对表情变化具有鲁棒性的3D人脸识别算法一直是研究人员面临的挑战。解决这个问题的一种方法是利用表面上最稳定的部分。鼻腔区域在各种表情上相对恒定的结构使其对鲁棒性识别具有吸引力，并且在本文中，对鼻子三维形状特征的使用进行了评估。经过去噪、人脸裁剪和对齐后，对鼻子区域进行裁剪，并在其表面鲁棒地检测出16个地标。对地标相连，鼻腔表面形成75条曲线；这些曲线构成了特征集。选择不同表情和遮挡（由于眼镜）上最稳定的曲线并用于鼻子识别。Bosphorus数据集用于特征选择，FRGC v2.0用于鼻子识别。结果表明，对于505个不同的受试者和4879个样本，仅使用两个不同表达的训练样本，其一级识别率为82.58%，使用FRGC v2.0数据集Spring2003文件夹进行训练，使用Fall2003和Spring2004文件夹进行测试，对中性和变化表达的识别率分别为90.87%和81.61%。考虑到特征和匹配的相对较低的复杂性，不同的表达结果是令人鼓舞的。
The development of 3D face recognition algorithms that are robust to variations in expression has been a challenge for researchers over the past decade. One approach to this problem is to utilize the most stable parts on the face surface. The nasal region's relatively constant structure over various expressions makes it attractive for robust recognition and, in this paper, the use of features from the three-dimensional shape of nose is evaluated. After denoising, face cropping and alignment, the nose region is cropped and 16 landmarks robustly detected on its surface. Pairs of landmarks are connected, which results in 75 curves on the nasal surface; these curves form the feature set. The most stable curves over different expressions and occlusions (due to glasses) are selected and used for nose recognition. The Bosphorus dataset is used for feature selection and FRGC v2.0 for nose recognition. Results show a rank-one recognition rate of 82.58% using only two training samples with varying expression for 505 different subjects and 4879 samples, and 90.87% and 81.61% using the FRGC v2.0 dataset Spring2003 folder for training and the Fall2003 and Spring2004 folders for testing, for neutral and varying expressions, respectively. Given the relatively low complexity of the features and matching, the varying expression results are encouraging.