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    • 72. 发明授权
    • Method and apparatus for red-eye detection in an acquired digital image based on image quality pre and post filtering
    • 基于图像质量前后滤波的获取的数字图像中的红眼检测方法和装置
    • US07436998B2
    • 2008-10-14
    • US11123971
    • 2005-05-06
    • Eran SteinbergPeter CorcoranYury PrilutskyPetronel BigioiFlorin Nanu
    • Eran SteinbergPeter CorcoranYury PrilutskyPetronel BigioiFlorin Nanu
    • G06K9/00
    • H04N1/62G06K9/0061G06T5/005G06T5/008G06T7/90G06T2207/30216H04N1/624
    • A method for red-eye detection in an acquired digital image comprises acquiring a first image and analyzing the first acquired image to provide characteristics indicative of image quality. The process then determines if one or more corrective processes can be beneficially applied to the first acquired image according to the characteristics. Any such corrective processes are applied and red-eye defects are detected in an established order established according to determination and analysis of characteristics of the corrective process and/or resulting image qualities. Defect correction can comprise applying one or more image correction operations, or a chain of two or more red-eye filters to the first acquired image. In this case, prior to the detecting step, it is determined if the red-eye filter or red eye filter chain should be applied before or after image corrective processes and whether the red eye filter can be adapted in accordance with the characteristics. The red-eye filter and the order in which it is executed in relation to the various image corrective operations may be adapted accordingly.
    • 所获取的数字图像中的红眼检测方法包括获取第一图像并分析第一获取图像以提供指示图像质量的特征。 然后,该过程确定是否可以根据特征将一个或多个校正过程有益地应用于第一获取的图像。 应用任何这样的校正过程,并且按照根据校正过程的特性的确定和分析建立的既定顺序和/或所得到的图像质量来检测红眼缺陷。 缺陷校正可以包括将一个或多个图像校正操作或两个或更多个红眼滤波器的链应用于第一获取的图像。 在这种情况下,在检测步骤之前,确定在图像校正处理之前或之后是否应用红眼滤波器或红眼滤波器链,以及是否可以根据特性适配红眼滤波器。 可以相应地调整红眼滤波器及其相对于各种图像校正操作执行它的顺序。
    • 80. 发明申请
    • Face Recognition with Combined PCA-Based Datasets
    • 基于PCA的数据集的人脸识别
    • US20080031498A1
    • 2008-02-07
    • US11833224
    • 2007-08-02
    • Peter CorcoranGabriel N. Costache
    • Peter CorcoranGabriel N. Costache
    • G06K9/00
    • G06K9/6247G06K9/00275G06K9/629
    • A face recognition method for working with two or more collections of facial images is provided. A representation framework is determined for a first collection of facial images including at least principle component analysis (PCA) features. A representation of said first collection is stored using the representation framework. A modified representation framework is determined based on statistical properties of original facial image samples of a second collection of facial images and the stored representation of the first collection. The first and second collections are combined without using original facial image samples. A representation of the combined image collection (super-collection) is stored using the modified representation framework. A representation of a current facial image, determined in terms of the modified representation framework, is compared with one or more representations of facial images of the combined collection. Based on the comparing, it is determined which, if any, of the facial images within the combined collection matches the current facial image.
    • 提供了一种用于处理两个或更多个面部图像集合的面部识别方法。 针对包括至少主成分分析(PCA)特征的面部图像的第一集合确定表示框架。 使用表示框架存储所述第一集合的表示。 基于面部图像的第二集合的原始面部图像样本的统计特性和第一集合的存储表示来确定修改后的表示框架。 组合第一和第二集合而不使用原始面部图像样本。 使用修改的表示框架存储组合图像集合(超级集合)的表示。 将根据修改的表示框架确定的当前面部图像的表示与组合集合的面部图像的一个或多个表示进行比较。 基于比较,确定组合集合中的哪个面部图像(如果有的话)与当前面部图像匹配。