Outdoor Face Recognition Using Enhanced Near Infrared Imaging

Dong, Yi; Liu, Rong; Chu, Rufeng; Wang, Rui; Liu, Dong; Li, Stan Z.

doi:10.1007/978-3-540-74549-5_44

Cited by 10 publications

(2 citation statements)

References 12 publications

(19 reference statements)

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“…The method achieved a verification rate of 90% at FAR=0.001 and 95% at FAR=0.01 on a database with 870 subjects. The same method was utilized with Enhanced NIR images for face verification outdoor, especially in sunlight [83]. Pan et al [86] proposed to improve the robustness of this work to variations of pose.…”

Section: Face Recognitionmentioning

confidence: 99%

Local Binary Patterns and Its Application to Facial Image Analysis: A Survey

Huang¹,

Shan²,

Ardabilian³

et al. 2011

IEEE Trans. Syst., Man, Cybern. C

796

343

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International audienceLocal Binary Patterns (LBP) is a non-parametric descriptor whose aim is to efficiently summarize the local structures of images. In recent years, it has aroused increasing interest in many areas of image processing and computer vision, and has shown its effectiveness in a number of applications, in particular for facial image analysis, including tasks as diverse as face detection, face recognition, facial expression analysis, demographic classification, etc. This paper presents a comprehensive survey of LBP metho-dology including several more recent variations. As a typical ap-plication of the LBP approach, LBP-based facial image analysis is extensively reviewed, while its successful extensions in dealing with various tasks of facial image analysis are also highlighted

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Section: Face Recognitionmentioning

confidence: 99%

Local Binary Patterns and Its Application to Facial Image Analysis: A Survey

Huang¹,

Shan²,

Ardabilian³

et al. 2011

IEEE Trans. Syst., Man, Cybern. C

796

343

View full text Add to dashboard Cite

show abstract

“…Indeed, NIR imaging has issue to properly deal with such conditions, and does not provide good quality images. This may be due to the stronger nearinfrared components contained in sunlight [41].…”

Section: Evaluation In the Near-infrared Spectrummentioning

confidence: 99%

A Comprehensive Experimental and Reproducible Study on Selfie Biometrics in Multistream and Heterogeneous Settings

Heusch

Pereira

Marcel

2019

IEEE Trans. Biom. Behav. Identity Sci.

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This contribution presents a new database to address current challenges in face recognition. It contains face video sequences of 75 individuals acquired either through a laptop webcam or when mimicking the front-facing camera of a smartphone. Sequences have been acquired with a device allowing to record visual, near-infrared and depth data at the same time. Recordings have been made across three sessions with different, challenging illumination conditions and variations in pose. Together with the database, several experimental protocols are provided and correspond to real world scenarios, when a mismatch in conditions between enrollment and probe images occurs. A comprehensive set of baseline experiments using publicly available baseline algorithms show that extreme illumination conditions and pose variations are remaining issues. However, the usage of different data domains-and their fusion-allows to mitigate such variation. Finally, experiments on heterogeneous face recognition are also presented using a state-of-the-art model based on deep neural networks, and showed better performance. When applied to other tasks, this model proved to surpass all existing baselines as well. The data, as well as the code to reproduce all experiments are made publicly available to help foster research in selfie biometrics using latest imaging devices.

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