Marker-less Facial Motion Capture based on the Parts Recognition.
Marker-less Facial Motion Capture based on the Parts Recognition.
复制标题
基于部位识别的无标记面部动作捕捉。
DOI：
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Hiroshi Kawasaki
中科院分区：
文献类型：
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作者：
Yasuhiro Akagi;Furukawa Ryo;Ryusuke Sagawa;Koichi Ogawara;Hiroshi Kawasaki
一种运动捕捉方法用于捕捉面部运动以创建3D动画和用于识别面部表情。由于面部运动由皮肤的非刚性变形组成，因此很难跟踪面部上一个点随时间的过渡。因此，人们提出了一些基于标记的方法来解决这一问题。然而，由于难以将标记放置在人脸或人脸的实际纹理上，因此难以应用基于标记的捕获方法。为了克服这个问题，我们提出了一种无标记的面部动作捕捉方法。由于每个面部部位的皮肤厚度不同，因此每个部位的运动特征也不同。这些特征使得非刚性跟踪问题更加困难。为了防止这个问题，我们使用随机森林算法从人脸的三维点识别出五种类型的面部部位（鼻子、嘴巴、眼睛、脸颊和障碍物）。人脸识别完成后，采用基于高斯混合模型的非刚性配准算法对人脸各部分的运动进行跟踪。由于每个部分的运动是独立检测的，因此我们将每个部分的运动整合为3D形状变形，以跟踪整个面部上点的运动。我们采用了一种基于径向基函数的自由变形技术进行积分。该方法利用非刚性配准算法检测到的关键点对：源面若干个点和目标形状对应点，实现三维形状的无缝变形。最后，我们将人脸的运动表示为从初始帧的人脸到其他帧的变形。在我们的结果中，我们表明，所提出的方法使我们能够更准确地检测到面部的运动。
A motion capture method is used to capture facial motion to create 3D animations and for recognizing facial expressions. Since the facial motion consists of non-rigid deformations of a skin, it is difficult to track a transition of a point on the face over time. Therefore, a number of methods based on markers have been proposed to solve this problem. However, since it is difficult to place the markers on a face or on an actual texture of the face, it is difficult to apply the marker-based capture methods. To overcome this problem, we propose a marker-less motion capture method for facial motions. Since the thickness of a skin varies in each facial part, the features of the motion of the each parts also vary. These features make the non-rigid tracking problem more difficult. To prevent the problem, we recognize five types of facial parts (nose, mouth, eye, cheek and obstacle) from 3D points of a face by using Random Forest algorithm. After the recognition of the facial parts, we track the motion of the each part by using a non-rigid registration algorithm based on the Gaussian Mixture Model. Since the motions of the each part are independently detected, we integrate the motions of the each part as 3D shape deformations for tracking the motions of the points on the whole face. We adopt a Free-Form Deformation technique which is based on the Radial Basis Function for the integration. This deformation method deforms 3D shapes seamlessly with pairs of key points: several numbers of points of a source face and the corresponding points of a target shape which are detected by the non-rigid registration algorithm. Finally, we represent the motion of the face as the deformation from the face of the initial frame to the others. In our results, we show that the proposed method enables us to detect the motion of the face more accurately.
DOI：
10.1109/tpami.2010.223
发表时间：
2011-08-01
影响因子：
23.6
作者：
Jian, Bing;Vemuri, Baba C.
通讯作者：
Vemuri, Baba C.