Abstract
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 language | English |
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Pages (from-to) | 3750-3766 |
Number of pages | 17 |
Journal | Pattern Recognition |
Volume | 47 |
Issue number | 12 |
DOIs | |
Publication status | Published - 2014 Dec 1 |
Keywords
- 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