Nighttime face recognition at large standoff: Cross-distance and cross-spectral matching

Dongoh Kang, Hu Han, Anil K. Jain, Seong Whan Lee

Research output: Contribution to journalArticlepeer-review

69 Citations (Scopus)


Face recognition in surveillance systems is important for security applications, especially in nighttime scenarios when the subject is far away from the camera. However, due to the face image quality degradation caused by large camera standoff and low illuminance, nighttime face recognition at large standoff is challenging. In this paper, we report a system that is capable of collecting face images at large standoff in both daytime and nighttime, and present an augmented heterogeneous face recognition (AHFR) approach for cross-distance (e.g., 150 m probe vs. 1 m gallery) and cross-spectral (near-infrared probe vs. visible light gallery) face matching. We recover high-quality face images from degraded probe images by proposing an image restoration method based on Locally Linear Embedding (LLE). The restored face images are matched to the gallery by using a heterogeneous face matcher. Experimental results show that the proposed AHFR approach significantly outperforms the state-of-the-art methods for cross-spectral and cross-distance face matching.

Original languageEnglish
Pages (from-to)3750-3766
Number of pages17
JournalPattern Recognition
Issue number12
Publication statusPublished - 2014 Dec 1

Bibliographical note

Publisher Copyright:
© 2014 Elsevier Ltd.


  • Cross-distance matching
  • Cross-spectral matching
  • Heterogeneous face matching
  • Image restoration
  • K-means clustering
  • Locally Linear Embedding (LLE)
  • Nighttime face recognition

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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