• Title, Summary, Keyword: Face super-resolution (SR)

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A Novel Algorithm for Face Recognition From Very Low Resolution Images

  • Senthilsingh, C.;Manikandan, M.
    • Journal of Electrical Engineering and Technology
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    • v.10 no.2
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    • pp.659-669
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    • 2015
  • Face Recognition assumes much significance in the context of security based application. Normally, high resolution images offer more details about the image and recognizing a face from a reasonably high resolution image would be easier when compared to recognizing images from very low resolution images. This paper addresses the problem of recognizing faces from a very low resolution image whose size is as low as $8{\times}8$. With the use of CCTV(Closed Circuit Television) and with other surveillance camera-based application for security purposes, the need to overcome the shortcomings with very low resolution images has been on the rise. The present day face recognition algorithms could not provide adequate performance when employed to recognize images from VLR images. Existing methods use super-resolution (SR) methods and Relation Based Super Resolution methods to construct from very low resolution images. This paper uses a learning based super resolution method to extract and construct images from very low resolution images. Experimental results show that the proposed SR algorithm based on relationship learning outperforms the existing algorithms in public face databases.

Preprocessing Methods for Low-Resolution Face Image Recognition (저해상도 영상 얼굴인식을 위한 전처리 방법)

  • Lee, Philku;Kim, Tai Yoon;Lee, Dasol;Kim, Seongjai
    • Proceedings of the Korea Information Processing Society Conference
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    • pp.781-784
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    • 2017
  • Face recognition systems are characterized by low invasiveness of acquisition, and increasingly better reliability. Such systems may not be applied effectively, when the images are in low resolution (LR) as in the case that photos are taken from long distances, typically public surveillance. In theory, the high resolution (HR) image reconstructed from an LR face image, applying a super resolution (SR) method, can be used for face recognition. However, existing face SR algorithms may not give satisfactory results in face recognition. This article investigates the very low resolution face recognition problem and introduces a partial differential equation (PDE)-based SR method for a face recognition system of convolutional neural network (CNN).

Reconstructing 3-D Facial Shape Based on SR Imagine

  • Hong, Yu-Jin;Kim, Jaewon;Kim, Ig-Jae
    • Journal of International Society for Simulation Surgery
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    • v.1 no.2
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    • pp.57-61
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    • 2014
  • We present a robust 3D facial reconstruction method using a single image generated by face-specific super resolution technique. Based on the several consecutive frames with low resolution, we generate a single high resolution image and a three dimensional facial model based on it. To do this, we apply PME method to compute patch similarities for SR after two-phase warping according to facial attributes. Based on the SRI, we extract facial features automatically and reconstruct 3D facial model with basis which selected adaptively according to facial statistical data less than a few seconds. Thereby, we can provide the facial image of various points of view which cannot be given by a single point of view of a camera.