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UNCONSTRAINED EAR RECOGNITION USING A COMBINATION OF DEEP LEARNING AND HANDCRAFTED FEATURES

机译:结合深度学习和精心设计的功能,实现无限制的耳朵识别

摘要

A system and method for identifying a subject based upon ear recognition using a convolutional neural network (CNN) and handcrafted features, wherein an ear in an image is cropped using ground truth annotations and landmark detection is performed to obtain the information required to normalize pose and scale variations. The normalized images are then described by different feature extractors and matched through distance metrics. Finally, scores are fused and a subject identification decision is made.
机译:一种使用卷积神经网络(CNN)和手工特征基于耳朵识别来识别对象的系统和方法,其中使用地面真相注释裁剪图像中的耳朵,并执行界标检测以获得归一化姿势和姿态所需的信息。规模变化。然后由不同的特征提取器描述归一化的图像,并通过距离度量进行匹配。最后,对分数进行融合,并做出主题识别决策。

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