Image classification method and apparatus

    公开(公告)号:US12131521B2

    公开(公告)日:2024-10-29

    申请号:US17587284

    申请日:2022-01-28

    CPC classification number: G06V10/764 G06F17/16 G06N3/02 G06V10/7715 G06V10/82

    Abstract: This application relates to an image recognition technology in the field of computer vision of artificial intelligence, and provides an image classification method and apparatus. An example method includes obtaining an input feature map of a to-be-processed image, and then performing feature extraction processing on the input feature map based on a feature extraction kernel of a neural network to obtain an output feature map, where each of a plurality of output sub-feature maps is determined based on the corresponding input sub-feature map and the feature extraction kernel, at least one of the output sub-feature maps is determined based on a target matrix obtained after an absolute value is taken, and a difference between the target matrix and the input sub-feature map corresponding to the target matrix is the feature extraction kernel. The to-be-processed image is classified based on the output feature map to obtain a classification result of the to-be-processed image.

    DATA FEATURE EXTRACTION METHOD AND RELATED APPARATUS

    公开(公告)号:US20230143985A1

    公开(公告)日:2023-05-11

    申请号:US18148304

    申请日:2022-12-29

    CPC classification number: G06N3/084 G06N3/0464 G06V10/82

    Abstract: A data feature extraction method and apparatus in the field of artificial intelligence are provided. An addition convolution operation is performed to extract a target feature in quantized data based on quantized feature extraction parameters, that is, to calculate a sum of absolute values of differences between the quantized feature extraction parameters and the quantized data, to obtain the target feature based on the sum. In addition, feature extraction parameters and data are quantized by using a same quantization parameter. According to this application, a storage resource is saved, a computing resource is saved, thereby reducing a limitation on an application of artificial intelligence to a resource-limited device. Further, when the extracted feature data is dequantized, the feature data may be dequantized based on the quantization parameters.

    METHOD AND APPARATUS FOR DETERMINING IDENTITY IDENTIFIER OF FACE IN FACE IMAGE, AND TERMINAL

    公开(公告)号:US20170300744A1

    公开(公告)日:2017-10-19

    申请号:US15639220

    申请日:2017-06-30

    CPC classification number: G06K9/00288 G06K9/00 G06K9/00268 G06K9/6278

    Abstract: The present invention provides a method and an apparatus for determining an identity identifier of a face in a face image, and a terminal. The method includes: obtaining an original feature vector of a face image; selecting k candidate vectors from a face image database; selecting a matching vector of the original feature vector from the k candidate vectors; and determining, an identity identifier that is of the matching vector. In embodiments of the present invention, a face image database stores a medium-level feature vector formed by means of mutual interaction between a low-level face feature vector and autocorrelation and cross-correlation submatrices in a joint Bayesian probability matrix. The medium-level feature vector includes information about mutual interaction between the face feature vector and the autocorrelation and cross-correlation submatrices in the joint Bayesian probability matrix, so that efficiency and accuracy of facial recognition can be improved.

    Image Processing Method And Apparatus
    16.
    发明申请
    Image Processing Method And Apparatus 审中-公开
    图像处理方法和装置

    公开(公告)号:US20170039761A1

    公开(公告)日:2017-02-09

    申请号:US15296138

    申请日:2016-10-18

    Abstract: An image processing method and apparatus are disclosed. The method includes obtaining a two-dimensional target face image, receiving an identification curve marked by a user in the target face image, locating a facial contour curve of a face from the target face image according to the identification curve and by using an image segmentation technology, determining a three-dimensional posture and a feature point position of the face in the target face image, and constructing a three-dimensional shape of the face in the target face image according to the facial contour curve, the three-dimensional posture, and the feature point position of the face in the target face image by using a preset empirical model of a three-dimensional face shape and a target function matching the empirical model of the three-dimensional face shape. Using the method and apparatus, the complexity of three-dimensional face shape construction can be reduced.

    Abstract translation: 公开了一种图像处理方法和装置。 该方法包括:获取二维目标人脸图像,接收由目标脸部图像中的用户标记的识别曲线,根据识别曲线从目标人脸图像定位面部的面部轮廓曲线,并通过使用图像分割 确定目标面部图像中的面部的三维姿态和特征点位置,根据面部轮廓曲线,三维姿势,面部轮廓曲线构成面部的三维形状, 以及通过使用三维脸部形状的预设经验模型和与三维脸部形状的经验模型相匹配的目标函数,在目标脸部图像中的脸部的特征点位置。 使用该方法和装置,可以减少三维面形结构的复杂性。

    Method and Apparatus for Generating Facial Feature Verification Model
    17.
    发明申请
    Method and Apparatus for Generating Facial Feature Verification Model 有权
    用于生成面部特征验证模型的方法和装置

    公开(公告)号:US20160070956A1

    公开(公告)日:2016-03-10

    申请号:US14841928

    申请日:2015-09-01

    CPC classification number: G06K9/00288 G06K9/00268 G06K9/6232

    Abstract: A method and an apparatus for generating a facial feature verification model. The method includes acquiring N input facial images, performing feature extraction on the N input facial images, to obtain an original feature representation of each facial image, and forming a face sample library, for samples of each person with an independent identity, obtaining an intrinsic representation of each group of face samples in at least two groups of face samples, training a training sample set of the intrinsic representation, to obtain a Bayesian model of the intrinsic representation, and obtaining a facial feature verification model according to a preset model mapping relationship and the Bayesian model of the intrinsic representation. In the method and apparatus for generating a facial feature verification model in the embodiments of the present disclosure, complexity is low and a calculation amount is small.

    Abstract translation: 一种用于生成面部特征验证模型的方法和装置。 该方法包括获取N个输入的面部图像,对N个输入的面部图像执行特征提取,以获得每个面部图像的原始特征表示,以及形成一个具有独立身份的每个人的样本的面部样本库, 在至少两组面部样本中对每组面部样本的表示,训练内在表示的训练样本集合,以获得内在表示的贝叶斯模型,并且根据预设模型映射关系获得面部特征验证模型 和贝叶斯模型的内在表征。 在本公开的实施例中用于生成面部特征验证模型的方法和装置中,复杂度低,计算量小。

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