幻觉空间关系学习,提高非常低分辨率的人脸识别

Juhyun Ahn, Daijin Kim, S. I. Ch'ng
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引用次数: 0

摘要

众所周知,人脸识别率受到探测图像分辨率的影响。因此,人们自然会期望通过人脸幻觉来提高分辨率,从而提高识别率。然而,以往的研究都认为视觉质量的提高并不一定会带来更好的识别率,在使用极低分辨率(VLR)图像时,人脸幻觉的识别效果尤其差。本文的实验结果表明,视觉质量与识别率之间存在相关性。提出了一种鲁棒性强的幻觉空间关系学习算法,以提高视觉质量和识别率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hallucination space relationship learning to improve very low resolution face recognition
It is known that face recognition rate is affected by the resolution of probe image. Therefore it is natural to expect improving the resolution via face hallucination would increase the recognition rate. However, it was concluded in the previous works that improvement in the visual quality does not necessarily lead to a better recognition rate, and performance of face hallucination for recognition is especially poor when very low resolution (VLR) images are used. Experiment results in this paper will show that there is a correlation between visual quality and recognition rate. And hallucination space relationship learning algorithm is proposed which is robust on hallucinating VLR images to improve the performance in terms of both visual quality and recognition rate.
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