Name
Abstract | ||
|---|---|---|
In this paper, we propose a simple but effective spatial co-occurrence of local intensity order (CoLIO) feature for face recognition. Local intensity order (LIO) is robust to illumination variance. Spatial co-occurrence of LIO not only preserves great invariance to illumination, but also greatly enhances the discriminative power of the descriptor as Co- LIO well captures the correlation between locally adjacent regions. The proposed feature has been successfully applied to two widely used face databases including AR [1] and LFW [2]. Superior performance on these two databases fully demonstrates the effectiveness of the proposed feature. Meanwhile, the extremely fast extraction speed makes the proposed feature practically useful. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICMEW.2013.6618447 | ICME Workshops |
Keywords | Field | DocType |
colio,illumination variance,face recognition,spatial co-occurrence,lfw,local intensity order,ar,spatial cooccurrence of local intensity order feature,feature extraction,face databases,fast extraction speed,face,databases,correlation,lighting | Computer vision,Facial recognition system,Invariant (physics),Three-dimensional face recognition,Pattern recognition,Computer science,Co-occurrence,Feature extraction,Artificial intelligence,Discriminative model,Face recognition feature extraction | Conference |
Volume | Issue | ISSN |
null | null | 2330-7927 |
Citations | PageRank | References |
3 | 0.40 | 11 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xianbiao Qi | 1 | 103 | 8.25 |
| Yi Lu | 2 | 3 | 0.40 |
| Shifeng Chen | 3 | 3 | 0.40 |
| Chun-Guang Li | 4 | 310 | 17.35 |
| Jun Guo | 5 | 1579 | 137.24 |