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Face_Transfer_with_Multilinear_Models
- Face Transfer is a method for mapping videorecorded perfor-mances of one individual to facial animations of another. It extracts visemes (speech-related mouth articulations), expressions, and three-dimensional (3D) pose from monocular video or 铿乴m fo
SRF
- In this paper, I present a novel hybrid face recognition approach based on a convolutional neural architecture, designed to robustly detect highly variable face patterns. With the weights of the trained neural networks there are created kernel window
Combining-face-detection-and-people-tracking-in-v
- Face detection algorithms are widely used in computer vision as they provide fast and reliable results depending on the application domain. A multi view approach is here presented to detect frontal and profile pose of people face using Histogram of
face-cvpr12
- 野外 人脸特征点定位和姿态估计 matlab 对应的 文章 源码已上传 希望 有兴趣的朋友可以共同 研究 和 探讨 配置到unix环境下-Wild facial feature points positioning and pose estimation matlab corresponding article hope interest friends can work together to study and explore
3-D-Models-Pose-and-Illumination
- The 3-D Morphable Model was introduced as a generative model to p redictthe appearances o f an individual while using a statistical prior on shape and texture allowin g its parameters to be estimated from single image. Based on these new unde
3D-models-
- 基于三维模型和仿射对应原理的人脸姿态估计方法-Based on 3D models and affine correspondence principle face pose estimation method
Face-Recognition-survey
- Face recognition has been one of the most interesting and important research fields in the past two decades. The reasons come the need of automatic recognitions and surveillance systems, the interest in human visual system on face recognition, and th
occlusion-refer2
- Face recognition [1], the least intrusive biometric technique in terms of acquisition, has been applied to a wide range of commercial and law enforcement applications. State-ofthe- art face recognition systems perform with high accuracy under
histogramOfGradients
- HOG PK Ali Hassan Ali Hassan opencv, MATLAB, Java, Android, Eclipse, XML, HTML,... Islamabad, Capital 0.0 New on Elance 22/hr rate About Ali Hassan I’m primarily interested Computer Vision and Image Processing projects. I hav
Facial_Feature_Tracking
- 通过建议一个人脸形状先验模型关注该问题，该模型基于受限Boltzmann Machines (RBM)及其变种构建。特别的，我们首先基于深度信任网络构建一个模型以获取接近正视角的表情变化的人脸形状变量。为了解决姿态变化问题，我们将正面人脸形状先验模型整合到一个3路（3-way）RBM模型，其可以获取正面人脸形状和非正面人脸形状间的关系。最后，我们建议一个方法，将人脸先验模型和人脸特征点的图像度量系统性地组合在一起。-we address this problem by proposing a
Robust_Face_Landmark
- 在现实世界条件下获取人脸存在较大的变化在形状和遮挡由于不同在姿态、表情、附属品的使用，例如，太阳镜和帽子以及与目标体（e.g. 食物）的交。当前的人脸界标估计方法在这种条件下努力但由于缺乏一种有效的理论方法用于处理局外点。我们提供了一个新奇的方法，称为Robust Cascaded Pose Regression (RCPR)，通过检测显式的遮挡且使用鲁棒的形状索引的特征可以减少exposure对于局外点。我们证明RCPR改进先前的界标估计方法在3个通用的人脸数据集上(LFPW, LFW and