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Makale detayı · 2003

Eigenface-domain super-resolution for face recognition

Dergi

IEEE Transactions on Image Processing
OpenAlex SJR Q1 JCR Q1 Atıf 338 Üst %10 Yüzdelik 97.3% FWCI 7.57
Yıl
2003
Tür
article

Veri kaynağı ayrımı

  • YÖKSİS dergi adı IEEE Transactions on Image Processing
  • OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)

Özet

OpenAlex · İngilizce

Face images that are captured by surveillance cameras usually have a very low resolution, which significantly limits the performance of face recognition systems. In the past, super-resolution techniques have been proposed to increase the resolution by combining information from multiple images. These techniques use super-resolution as a preprocessing step to obtain a high-resolution image that is later passed to a face recognition system. Considering that most state-of-the-art face recognition systems use an initial dimensionality reduction method, we propose to transfer the super-resolution reconstruction from pixel domain to a lower dimensional face space. Such an approach has the advantage of a significant decrease in the computational complexity of the super-resolution reconstruction. The reconstruction algorithm no longer tries to obtain a visually improved high-quality image, but instead constructs the information required by the recognition system directly in the low dimensional domain without any unnecessary overhead. In addition, we show that face-space super-resolution is more robust to registration errors and noise than pixel-domain super-resolution because of the addition of model-based constraints.

Konular

Atıflar

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338 atıf

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