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    • 9. 发明申请
    • LOW-COST FACE RECOGNITION USING GAUSSIAN RECEPTIVE FIELD FEATURES
    • 使用高斯接收场特征的低成本脸部识别
    • WO2016154781A1
    • 2016-10-06
    • PCT/CN2015/075190
    • 2015-03-27
    • INTEL CORPORATIONLI, JianguoCHEN, YurongCHEN, KeCHIU, Ye-Jen
    • LI, JianguoCHEN, YurongCHEN, KeCHIU, Ye-Jen
    • G06K9/00
    • G06K9/00281G06K9/00288G06K9/4619G06K9/6228G06K9/623
    • Methods and systems may provide for facial recognition of at least one input image utilizing hierarchical feature learning and pair-wise classification. Receptive field theory may be used on the input image to generate a pre-processed multi-channel image. Channels in the pre-processed image may be activated based on the amount of feature rich details within the channels. Similarly, local patches may be activated based on the discriminant features within the local patches. Features may be extracted from the local patches and the most discriminant features may be selected in order to perform feature matching on pair sets. The system may utilize patch feature pooling, pair-wise matching,and large-scale training in order to quickly and accurately perform facial recognition at a low cost for both system memory and computation.
    • 方法和系统可以使用分层特征学习和成对分类来提供对至少一个输入图像的面部识别。 可以在输入图像上使用接受场理论来生成预处理的多通道图像。 可以基于频道内的特征丰富的细节的数量来激活预处理图像中的频道。 类似地,可以基于局部补丁内的判别特征激活局部补丁。 可以从局部斑块中提取特征,并且可以选择最多的判别特征,以便在对集上执行特征匹配。 系统可以利用补丁特征池,成对匹配和大规模训练,以便以低成本快速准确地执行系统内存和计算的面部识别。