FaceWarehouse: A 3D Facial Expression Database for Visual Computing
FaceWarehouse: A 3D Facial Expression Database for Visual Computing
复制标题
FaceWarehouse：用于视觉计算的 3D 面部表情数据库
DOI：
10.1109/tvcg.2013.249
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发表时间：
2014-03-01
影响因子：
5.2
通讯作者：
Zhou, Kun
中科院分区：
文献类型：
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作者：
Cao, Chen;Weng, Yanlin;Zhou, Kun
我们提出FaceWarehouse，一个用于视觉计算应用的3D面部表情数据库。我们使用Kinect，一个现成的RGBD相机，捕捉150个7-80岁的人，来自不同的种族背景。对于每个人，我们捕获了她不同表情的RGBD数据，包括中性表情和19个其他表情，如张嘴，微笑，亲吻等。对于每个RGBD原始数据记录，彩色图像上的一组面部特征点，如眼角，嘴巴轮廓和鼻尖自动定位，如果需要更好的精度，则手动调整。然后，我们将模板面部网格变形以尽可能接近地拟合深度数据，同时将彩色图像上的特征点与网格上的对应点进行匹配。从这些拟合的人脸网格开始，我们为每个人构建了一组个人特定的表情混合形状。这些具有一致拓扑结构的网格被组装成一个秩为3的张量，以构建一个具有两个属性的双线性人脸模型：身份和表情。与以前的3D人脸数据库相比，对于我们数据库中的每个人，都有更丰富的表情匹配集合，可以描述大多数人类面部动作。我们展示了FaceWarehouse的视觉计算与四个应用程序的潜力：面部图像操作，面部组件传输，基于性能的实时面部图像动画，面部动画重定向从视频到图像。
We present FaceWarehouse, a database of 3D facial expressions for visual computing applications. We use Kinect, an off-the-shelf RGBD camera, to capture 150 individuals aged 7-80 from various ethnic backgrounds. For each person, we captured the RGBD data of her different expressions, including the neutral expression and 19 other expressions such as mouth-opening, smile, kiss, etc. For every RGBD raw data record, a set of facial feature points on the color image such as eye corners, mouth contour, and the nose tip are automatically localized, and manually adjusted if better accuracy is required. We then deform a template facial mesh to fit the depth data as closely as possible while matching the feature points on the color image to their corresponding points on the mesh. Starting from these fitted face meshes, we construct a set of individual-specific expression blendshapes for each person. These meshes with consistent topology are assembled as a rank-3 tensor to build a bilinear face model with two attributes: identity and expression. Compared with previous 3D facial databases, for every person in our database, there is a much richer matching collection of expressions, enabling depiction of most human facial actions. We demonstrate the potential of FaceWarehouse for visual computing with four applications: facial image manipulation, face component transfer, real-time performance-based facial image animation, and facial animation retargeting from video to image.