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    • 9. 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。
    • 10. 发明申请
    • METHOD OF DETECTING FACIAL ATTRIBUTES
    • 检测真菌属性的方法
    • US20140003663A1
    • 2014-01-02
    • US13997310
    • 2011-04-11
    • Jianguo LiTao WangYangzhou DuQiang Li
    • Jianguo LiTao WangYangzhou DuQiang Li
    • G06K9/00
    • G06K9/00228G06K9/00241G06K9/00281
    • Detection of a facial attribute such as a smile or gender in a human face in an image is performed by embodiments of the present invention in a computationally efficient manner. First, a face in the image is detected to produce a facial image. Facial landmarks are detected in the facial image. The facial image is aligned and normalized based on the detected facial landmarks to produce a normalized facial image. Local features from selected local regions are extracted from the normalized facial image. A facial attribute is predicted in each selected local region by inputting each selected local feature into a weak classifier having a multi-layer perceptron (MLP) structure. Finally, output data is aggregated from each weak classifier component to generate all indication that the facial attribute is detected in the facial image.
    • 通过本发明的实施例以计算上有效的方式来检测图像中的人脸中的笑脸或性别的面部属性。 首先,检测图像中的脸部以产生面部图像。 在面部图像中检测到面部地标。 基于检测到的面部地标对面部图像进行对准和归一化,以产生归一化的面部图像。 从标准化的面部图像中提取来自所选择的局部区域的局部特征。 通过将每个选定的局部特征输入到具有多层感知器(MLP)结构的弱分类器中,在每个选定的局部区域中预测面部属性。 最后,从每个弱分类器组件聚合输出数据,以产生在面部图像中检测到面部属性的所有指示。