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    • 6. 发明申请
    • Method of performing shape localization
    • 执行形状定位的方法
    • US20060008149A1
    • 2006-01-12
    • US10889459
    • 2004-07-12
    • Jilin TuThomas Huang
    • Jilin TuThomas Huang
    • G06K9/46G06K9/36
    • G06K9/6209G06K9/00248
    • A method for performing shape localization in an image includes deriving a model shape from a database of a plurality of sample shapes. The model shape is defined by a set of landmarks. The method further includes deriving a texture likelihood model of present sub-patches of the set of landmarks defining the model shape in the image, and proposing a new set of landmarks that approximates a true location of features of the shape based on a sample proposal model of the present sub-patches. A CONDENSATION algorithm is used to derive the texture likelihood model and the proposed new set of landmarks.
    • 用于在图像中执行形状定位的方法包括从多个样本形状的数据库导出模型形状。 模型形状由一组地标定义。 该方法还包括导出定义图像中的模型形状的一组地标中的当前子块的纹理似然模型,并且基于样本提案模型提出近似于形状的特征的真实位置的新的地标集合 的当前子贴片。 使用CONDENSATION算法来导出纹理似然模型和提出的新的地标集。
    • 8. 发明授权
    • Optimal subspaces for face recognition
    • 面部识别的最佳子空间
    • US08498454B2
    • 2013-07-30
    • US12627039
    • 2009-11-30
    • Jilin TuFrederick Wilson WheelerPeter Henry TuXiaoming LiuYan Tong
    • Jilin TuFrederick Wilson WheelerPeter Henry TuXiaoming LiuYan Tong
    • G06K9/00
    • G06K9/6234G06K9/00288G06K9/6215
    • A technique for optimizing object recognition is disclosed. The technique includes receiving at least one image of an object and at least one reference image. The technique further includes identifying at least one performance metric corresponding to an object recognition task. The identified performance metric is optimized to generate the corresponding optimized performance metric by determining an optimal subspace based on a determined objective function corresponding to the object recognition task and a difference between the received image and the corresponding reference image. Subsequently, the technique includes comparing the received image with the reference image based on the optimized performance metric for performing the object recognition task.
    • 公开了一种用于优化对象识别的技术。 该技术包括接收对象和至少一个参考图像的至少一个图像。 该技术还包括识别对应于对象识别任务的至少一个性能量度。 通过基于与对象识别任务相对应的确定的目标函数和接收到的图像与对应的参考图像之间的差异来确定最佳子空间来优化识别的性能度量以产生相应的优化性能度量。 随后,该技术包括基于用于执行对象识别任务的优化性能度量来比较接收到的图像与参考图像。