Real time head pose estimation
    2.
    发明授权
    Real time head pose estimation 有权
    实时头部姿态估计

    公开(公告)号:US08687880B2

    公开(公告)日:2014-04-01

    申请号:US13425188

    申请日:2012-03-20

    IPC分类号: G06K9/62

    摘要: Methods are provided for generating a low dimension pose space and using the pose space to estimate one or more head rotation angles of a user head. In one example, training image frames including a test subject head are captured under a plurality of conditions. For each frame an actual head rotation angle about a rotation axis is recorded. In each frame a face image is detected and converted to an LBP feature vector. Using principal component analysis a PCA feature vector is generated. Pose classes related to rotation angles about a rotation axis are defined. The PCA feature vectors are grouped into a pose class that corresponds to the actual rotation angle associated with the PCA feature vector. Linear discriminant analysis is applied to the pose classes to generate the low dimension pose space.

    摘要翻译: 提供了用于产生低维度姿态空间并且使用姿态空间来估计用户头部的一个或多个头部旋转角度的方法。 在一个示例中,在多个条件下捕获包括测试对象头的训练图像帧。 对于每个帧,记录关于旋转轴的实际头部旋转角度。 在每帧中,检测到脸部图像并将其转换为LBP特征向量。 使用主成分分析生成PCA特征向量。 定义与旋转轴相关的旋转角度的姿态类。 PCA特征向量被分组为与PCA特征向量相关联的实际旋转角度对应的姿态类别。 将线性判别分析应用于姿态类以生成低维姿态空间。

    REAL TIME HEAD POSE ESTIMATION
    3.
    发明申请
    REAL TIME HEAD POSE ESTIMATION 有权
    实时头枕估计

    公开(公告)号:US20130251244A1

    公开(公告)日:2013-09-26

    申请号:US13425188

    申请日:2012-03-20

    IPC分类号: G06K9/68 G06K9/62

    摘要: Methods are provided for generating a low dimension pose space and using the pose space to estimate one or more head rotation angles of a user head. In one example, training image frames including a test subject head are captured under a plurality of conditions. For each frame an actual head rotation angle about a rotation axis is recorded. In each frame a face image is detected and converted to an LBP feature vector. Using principal component analysis a PCA feature vector is generated. Pose classes related to rotation angles about a rotation axis are defined. The PCA feature vectors are grouped into a pose class that corresponds to the actual rotation angle associated with the PCA feature vector. Linear discriminant analysis is applied to the pose classes to generate the low dimension pose space.

    摘要翻译: 提供了用于产生低维度姿态空间并且使用姿态空间来估计用户头部的一个或多个头部旋转角度的方法。 在一个示例中,在多个条件下捕获包括测试对象头的训练图像帧。 对于每个帧,记录关于旋转轴的实际头部旋转角度。 在每帧中,检测到脸部图像并将其转换为LBP特征向量。 使用主成分分析生成PCA特征向量。 定义与旋转轴相关的旋转角度的姿态类。 PCA特征向量被分组为与PCA特征向量相关联的实际旋转角度对应的姿态类别。 将线性判别分析应用于姿态类以生成低维姿态空间。