US Patent Application 18313152. LOW-RESOLUTION FACE RECOGNITION DEVICE AND LOW-RESOLUTION FACE RECOGNIZER LEARNING DEVICE AND METHOD simplified abstract

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LOW-RESOLUTION FACE RECOGNITION DEVICE AND LOW-RESOLUTION FACE RECOGNIZER LEARNING DEVICE AND METHOD

Organization Name

ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor(s)

Hyungil Kim of Daejeon (KR)

Minho Park of Daejeon (KR)

Kang Min Bae of Daejeon (KR)

LOW-RESOLUTION FACE RECOGNITION DEVICE AND LOW-RESOLUTION FACE RECOGNIZER LEARNING DEVICE AND METHOD - A simplified explanation of the abstract

This abstract first appeared for US patent application 18313152 titled 'LOW-RESOLUTION FACE RECOGNITION DEVICE AND LOW-RESOLUTION FACE RECOGNIZER LEARNING DEVICE AND METHOD

Simplified Explanation

The present disclosure describes a low-resolution face recognition device that can accurately identify faces using both high-resolution and low-resolution images.

  • The device includes a high-resolution face image inputter and a low-resolution face image inputter to capture different quality images of faces.
  • A high-resolution face feature extractor is used to extract detailed features from the high-resolution and low-resolution face images.
  • A face quality feature extractor is used to assess the quality of the face images.
  • A feature combiner combines the high-resolution face feature and the face quality feature to detect the high-resolution and low-resolution face features.
  • A feature adaptation network extracts high-resolution and low-resolution face feature maps using the detected features.
  • A consistency meter measures the consistency of the face feature maps to determine a face ID, ensuring accurate face recognition.


Original Abstract Submitted

The present disclosure relates to a low-resolution face recognition device, which includes a high-resolution face image inputter; a low-resolution face image inputter; a high-resolution face feature extractor configured to extract a high-resolution face feature by using high-resolution and low-resolution face images; a face quality feature extractor configured to extract face quality features by using the high-resolution and low-resolution face images; a feature combiner configured to detect the high-resolution and low-resolution face features by concatenating the high-resolution face feature and the face quality feature; a feature adaptation network configured to extract a high-resolution face feature map and a low-resolution face feature map by using the detected high-resolution and low-resolution face features, respectively; and a consistency meter configured to determine a face ID by measuring consistency of a face feature map by using the extracted high-resolution and low-resolution face feature maps.

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