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    • 28. 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。
    • 29. 发明申请
    • TECHNIQUES FOR IMPROVED FEATURE DETECTION
    • 改进特征检测技术
    • US20140086490A1
    • 2014-03-27
    • US13625962
    • 2012-09-25
    • Qiang LiBin WangLiu Yang
    • Qiang LiBin WangLiu Yang
    • G06K9/46
    • G06K9/46
    • Techniques for improved feature detection are described. In one embodiment, for example, a device may include a processor circuit and a feature detection module, and the feature detection module may be operative on the processor circuit to perform a first feature detection iteration for a graphics information element using an integral pixel value array, determine a scaling factor, recalculate the integral pixel value array based on the scaling factor, and perform a second feature detection iteration for the graphics information element using the recalculated integral pixel value array. Other embodiments are described and claimed.
    • 描述了用于改进特征检测的技术。 在一个实施例中,例如,设备可以包括处理器电路和特征检测模块,并且特征检测模块可以在处理器电路上操作,以使用积分像素值阵列来执行图形信息元素的第一特征检测迭代 确定缩放因子,基于缩放因子重新计算积分像素值阵列,并且使用重新计算的积分像素值阵列对图形信息元素执行第二特征检测迭代。 描述和要求保护其他实施例。