Nuclear Norm Based Matrix Regression with Applications to Face Recognition with Occlusion and Illumination Changes

By Jian Yang, Lei Luo, Jianjun Qian, Ying Tai, Fanlong Zhang, Yong Xu. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014

350 citations recorded by the source corpus.

Recently, regression analysis has become a popular tool for face recognition. Most existing regression methods use the one-dimensional, pixel-based error model, which characterizes the representation error individually, pixel by pixel, and thus neglects the two-dimensional structure of the error image. We observe that occlusion and illumination changes generally lead, approximately, to a low-rank error image. In order to make use of this low-rank structural information, this paper presents a two-dimensional image-matrix-based error model, namely, nuclear norm based matrix regression (NMR), for face representation and classification. NMR uses the minimal nuclear norm of representation error image as a criterion, and the alternating direction method of multipliers (ADMM) to calculate the regression coefficients. We further develop a fast ADMM algorithm to solve the approximate NMR model and show it has a quadratic rate of convergence. We experiment using five popular face image databases: the Extended Yale B, AR, EURECOM, Multi-PIE and FRGC. Experimental results demonstrate the performance advantage of NMR over the state-of-the-art regression-based methods for face recognition in the presence of occlusion and illumination variations.

Subfields: Computational Mechanics, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/06625b0c5747ccb8524fec9f44e4a8aa1ecc2151

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Ying Tai
2. Libo Zhang
3. Yuqing Ma
4. Jian Yang
5. Xianglong Liu

In Computer Vision and Pattern Recognition

1. Ying Tai
2. Jian Yang
3. Xianglong Liu
4. Libo Zhang
5. Feiyue Huang
6. Renshuai Tao
7. Yanlu Wei
8. Chengjie Wang

Citations in the corpus

• Occluded Prohibited Items Detection: An X-ray Security Inspection Benchmark and De-occlusion Attention Module (2020, background): “There are several works trying to solve occlusion problems in different scenarios, such as person re-identification [24, 29, 30], face recognition [5, 17, 25].”
• DSFD: Dual Shot Face Detector (2018, background): “Face detection is a fundamental step for various facial applications, like face alignment [26], parsing [3], recognition [34], and verification [6].”