Proceedings ArticleDOI
Face identification from low resolution near-infrared images
Soumyadeep Ghosh,Rohit Keshari,Richa Singh,Mayank Vatsa +3 more
- pp 938-942
TLDR
It is shown that learned features contribute considerably to the performance of identification algorithm, and that using both feature level and score level fusion in a hierarchal approach gives good performance.Abstract:
Face identification from low quality and low resolution Near-Infrared (NIR) face images is a challenging problem. Since surveillance cameras typically acquire images at a large standoff distance, the effective resolution of the face is not large enough to identify the individuals. Moreover for a 24-hour surveillance footage, images in low light and at nighttime are acquired in NIR mode which makes the identification problem even more challenging. We propose an effective method using both hand-crafted and learned features for face identification of low resolution NIR images. We show that learned features contribute considerably to the performance of identification algorithm, and that using both feature level and score level fusion in a hierarchal approach gives good performance. The results demonstrate the effectiveness of the proposed approach on images which are of low quality, low resolution and acquired under challenging illumination conditions in near-infrared mode by surveillance cameras.read more
Citations
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Journal ArticleDOI
A survey on deep learning based face recognition
Guodong Guo,Guodong Guo,Na Zhang +2 more
TL;DR: Major deep learning concepts pertinent to face image analysis and face recognition are reviewed, and a concise overview of studies on specific face recognition problems is provided, such as handling variations in pose, age, illumination, expression, and heterogeneous face matching.
Journal ArticleDOI
Multi-view learning for visual violence recognition with maximum entropy discrimination and deep features
Shiliang Sun,Yuhan Liu,Liang Mao +2 more
TL;DR: This study applies multi-view learning to violent behavior recognition of still images, and can be useful for the research of network image or video information monitoring and filtering.
Proceedings ArticleDOI
Identity Aware Synthesis for Cross Resolution Face Recognition
TL;DR: The proposed Synthesis via Hierarchical Sparse Representation (SHSR) algorithm for synthesizing a high resolution face image from a low resolution input image demonstrates the efficacy of the proposed algorithm in terms of both face identification and image quality measures.
Journal ArticleDOI
Subclass Heterogeneity Aware Loss for Cross-Spectral Cross-Resolution Face Recognition
TL;DR: This paper proposes a Subclass Heterogeneity Aware Loss (SHEAL) to train a deep convolutional neural network model such that it produces embeddings suitable for heterogeneous face recognition, both single and multiple heterogeneities.
Journal ArticleDOI
SUPREAR-NET: Supervised Resolution Enhancement and Recognition Network
TL;DR: A Supervised Resolution Enhancement and Recognition Network (SUPREAR-NET), which does not corrupt the useful class-specific information of the face image and transforms a low resolution probe image into a high resolution one, followed by effective matching with the gallery using a trained discriminative model.
References
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Proceedings ArticleDOI
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