Cross-spectrum face recognition using subspace projection hashing

H Wang, X Dong, Z Jin, JL Dugelay… - … Conference on Pattern …, 2021 - ieeexplore.ieee.org
2020 25th International Conference on Pattern Recognition (ICPR), 2021ieeexplore.ieee.org
Cross-spectrum face recognition, eg visible to thermal matching, remains a challenging task
due to the large variation originated from different domains. This paper proposed a
subspace projection hashing (SPH) to enable the cross-spectrum face recognition task. The
intrinsic idea behind SPH is to project the features from different domains onto a common
subspace, where matching the faces from different domains can be accomplished. Notably,
we proposed a new loss function that can (i) preserve both inter-domain and intra-domain …
Cross-spectrum face recognition, e.g. visible to thermal matching, remains a challenging task due to the large variation originated from different domains. This paper proposed a subspace projection hashing (SPH) to enable the cross-spectrum face recognition task. The intrinsic idea behind SPH is to project the features from different domains onto a common subspace, where matching the faces from different domains can be accomplished. Notably, we proposed a new loss function that can (i) preserve both inter-domain and intra-domain similarity; (ii) regularize a scaled-up pairwise distance between hashed codes, to optimize projection matrix. Three datasets, Wiki, EURECOM VIS-TH paired face and TDFace are adopted to evaluate the proposed SPH. The experimental results indicate that the proposed SPH outperforms the original linear subspace ranking hashing (LSRH) in the benchmark dataset (Wiki) and demonstrates a reasonably good performance for visible-thermal, visible-near-infrared face recognition, therefore suggests the feasibility and effectiveness of the proposed SPH.
ieeexplore.ieee.org
顯示最佳搜尋結果。 查看所有結果