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    • 1. 发明授权
    • Method of facial landmark detection
    • 面部地标检测方法
    • US09471829B2
    • 2016-10-18
    • US13997296
    • 2011-03-31
    • Ang LiuYangzhou DuTao WangJianguo LiQiang LiYimin Zhang
    • Ang LiuYangzhou DuTao WangJianguo LiQiang LiYimin Zhang
    • G06K9/00G06K9/46G06K9/62
    • G06K9/00248G06K9/00281G06K9/6209
    • Detecting facial landmarks in a face detected in an image may be performed by first cropping a face rectangle region of the detected face in the image and generating an integral image based at least in part on the face rectangle region. Next, a cascade classifier may be executed for each facial landmark of the face rectangle region to produce one response image for each facial landmark based at least in part on the integral image. A plurality of Active Shape Model (ASM) initializations may be set up. ASM searching may be performed for each of the ASM initializations based at least in part on the response images, each ASM search resulting in a search result having a cost. Finally, a search result of the ASM searches having a lowest cost function may be selected, the selected search result indicating locations of the facial landmarks in the image.
    • 可以通过首先裁剪图像中检测到的面部的面部矩形区域并且至少部分地基于面部矩形区域来生成整体图像来检测在图像中检测到的面部中的面部界标。 接下来,可以对面部矩形区域的每个面部标记执行级联分类器,以至少部分地基于积分图像来为每个面部标记产生一个响应图像。 可以设置多个活动形状模型(ASM)初始化。 可以至少部分地基于响应图像来对每个ASM初始化执行ASM搜索,每个ASM搜索导致搜索结果具有成本。 最后,可以选择具有最低成本函数的ASM搜索的搜索结果,所选择的搜索结果指示图像中的面部地标的位置。
    • 2. 发明申请
    • TRACKING AND RECOGNITION OF FACES USING SELECTED REGION CLASSIFICATION
    • 使用选定区域分类来跟踪和识别
    • US20140241574A1
    • 2014-08-28
    • US13996496
    • 2011-04-11
    • Tao WangJianguo LiYangzhou DuQiang LiYimin Zhang
    • Tao WangJianguo LiYangzhou DuQiang LiYimin Zhang
    • G06K9/00
    • G06K9/00288G06K9/00221
    • Methods, apparatuses, and articles associated with facial tracking and recognition are disclosed. In embodiments, facial images may be detected in video or still images and tracked. After normalization of the facial images, feature data may be extracted from selected regions of the faces to compare to associated feature data in known faces. The selected regions may be determined using a boosting machine learning processes over a set of known images. After extraction, individual two-class comparisons may be performed between corresponding feature data from regions on the tested facial images and from the known facial image. The individual two-class classifications may then be combined to determine a similarity score for the tested face and the known face. If the similarity score exceeds a threshold, an identification of the known face may be output or otherwise used. Additionally, tracking with voting may be performed on faces detected in video. After a threshold of votes is reached, a given tracked face may be associated with a known face.
    • 公开了与面部跟踪和识别有关的方法,装置和文章。 在实施例中,可以在视频或静止图像中检测面部图像并进行跟踪。 在面部图像归一化之后,可以从面部的选定区域提取特征数据,以与已知面部中的相关特征数据进行比较。 可以使用一组已知图像上的升压机学习处理来确定所选择的区域。 提取后,可以在来自所测试的面部图像上的区域和来自已知面部图像的相应特征数据之间进行单独的两类比较。 然后可以组合个体两类分类以确定测试面部和已知面部的相似性得分。 如果相似性分数超过阈值,则可以输出或以其他方式使用已知面部的识别。 此外,可以对在视频中检测到的脸部进行投票跟踪。 在达成一个选票之后,一个给定的被追踪的面孔可能与一个已知的面孔相关联。
    • 4. 发明申请
    • METHOD OF FACIAL LANDMARK DETECTION
    • 方法地名检测方法
    • US20140050358A1
    • 2014-02-20
    • US13997296
    • 2011-03-31
    • Ang LiuYangzhou DuTao WangJianguo LiQiang LiYimin Zhang
    • Ang LiuYangzhou DuTao WangJianguo LiQiang LiYimin Zhang
    • G06K9/00
    • G06K9/00248G06K9/00281G06K9/6209
    • Detecting facial landmarks in a face detected in an image may be performed by first cropping a face rectangle region of the detected face in the image and generating an integral image based at least in part on the face rectangle region. Next, a cascade classifier may be executed for each facial landmark of the face rectangle region to produce one response image for each facial landmark based at least in part on the integral image. A plurality of Active Shape Model (ASM) initializations may be set up. ASM searching may be performed for each of the ASM initializations based at least in part on the response images, each ASM search resulting in a search result having a cost. Finally, a search result of the ASM searches having a lowest cost function may be selected, the selected search result indicating locations of the facial landmarks in the image.
    • 可以通过首先裁剪图像中检测到的面部的面部矩形区域并且至少部分地基于面部矩形区域来生成整体图像来检测在图像中检测到的面部中的面部界标。 接下来,可以对面部矩形区域的每个面部标记执行级联分类器,以至少部分地基于积分图像来为每个面部标记产生一个响应图像。 可以设置多个活动形状模型(ASM)初始化。 可以至少部分地基于响应图像来对每个ASM初始化执行ASM搜索,每个ASM搜索导致搜索结果具有成本。 最后,可以选择具有最低成本函数的ASM搜索的搜索结果,所选择的搜索结果指示图像中的面部地标的位置。
    • 6. 发明授权
    • Tracking and recognition of faces using selected region classification
    • 使用选择的区域分类来跟踪和识别面部
    • US09489567B2
    • 2016-11-08
    • US13996496
    • 2011-04-11
    • Tao WangJianguo LiYangzhou DuQiang LiYimin Zhang
    • Tao WangJianguo LiYangzhou DuQiang LiYimin Zhang
    • G06K9/00
    • G06K9/00288G06K9/00221
    • Methods, apparatuses, and articles associated with facial tracking and recognition are disclosed. In embodiments, facial images may be detected in video or still images and tracked. After normalization of the facial images, feature data may be extracted from selected regions of the faces to compare to associated feature data in known faces. The selected regions may be determined using a boosting machine learning processes over a set of known images. After extraction, individual two-class comparisons may be performed between corresponding feature data from regions on the tested facial images and from the known facial image. The individual two-class classifications may then be combined to determine a similarity score for the tested face and the known face. If the similarity score exceeds a threshold, an identification of the known face may be output or otherwise used. Additionally, tracking with voting may be performed on faces detected in video. After a threshold of votes is reached, a given tracked face may be associated with a known face.
    • 公开了与面部跟踪和识别有关的方法,装置和文章。 在实施例中,可以在视频或静止图像中检测面部图像并进行跟踪。 在面部图像归一化之后,可以从面部的选定区域提取特征数据,以与已知面部中的相关特征数据进行比较。 可以使用一组已知图像上的升压机学习处理来确定所选择的区域。 提取后,可以在来自所测试的面部图像上的区域和来自已知面部图像的相应特征数据之间进行单独的两类比较。 然后可以组合个体两类分类以确定测试面部和已知面部的相似性得分。 如果相似性分数超过阈值,则可以输出或以其他方式使用已知面部的识别。 此外,可以对在视频中检测到的脸部进行投票跟踪。 在达成一个选票之后,一个给定的被追踪的面孔可能与一个已知的面孔相关联。