Plenoptic Face Presentation Attack Detection

Zhu, Shuaishuai; Lv, Xiaoyang; Feng, Xiaohua; Lin, Jie; Jin, Peng; Gao, Liang

doi:10.1109/access.2020.2980755

Cited by 5 publications

References 35 publications

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A survey on face presentation attack detection mechanisms: hitherto and future perspectives

Sharma

Selwal

2023

Multimedia Systems

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The advances in human face recognition (FR) systems have recorded sublime success for automatic and secured authentication in diverse domains. Although the traditional methods have been overshadowed by face recognition counterpart during this progress, computer vision gains rapid traction, and the modern accomplishments address problems with real-world complexity. However, security threats in FR-based systems are a growing concern that offers a new-fangled track to the research community. In particular, recent past has witnessed ample instances of spoofing attacks where imposter breaches security of the system with an artifact of human face to circumvent the sensor module. Therefore, presentation attack detection (PAD) capabilities are instilled in the system for discriminating genuine and fake traits and anticipation of their impact on the overall behavior of the FR-based systems. To scrutinize exhaustively the current state-of-the-art efforts, provide insights, and identify potential research directions on face PAD mechanisms, this systematic study presents a review of face anti-spoofing techniques that use computational approaches. The study includes advancements in face PAD mechanisms ranging from traditional hardware-based solutions to up-to-date handcrafted features or deep learning-based approaches. We also present an analytical overview of face artifacts, performance protocols, and benchmark face anti-spoofing datasets. In addition, we perform analysis of the twelve recent state-of-the-art (SOTA) face PAD techniques on a common platform using identical dataset (i.e., REPLAY-ATTACK) and performance protocols (i.e., HTER and ACA). Our overall analysis investigates that despite prevalent face PAD mechanisms demonstrate potential performance, there exist some crucial issues that requisite a futuristic attention. Our analysis put forward a number of open issues such as; limited generalization to unknown attacks, inadequacy of face datasets for DL-models, training models with new fakes, efficient DL-enabled face PAD with smaller datasets, and limited discrimination of handcrafted features. Furthermore, the COVID-19 pandemic is an additional challenge to the existing face-based recognition systems, and hence to the PAD methods. Our motive is to present a complete reference of studies in this field and orient researchers to promising directions.

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A survey on face presentation attack detection mechanisms: hitherto and future perspectives

Sharma

Selwal

2023

Multimedia Systems

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A Dataset and Benchmark Towards Multi-Modal Face Anti-Spoofing Under Surveillance Scenarios

Chen

et al. 2021

IEEE Access

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Developing an optical design pipeline for correcting lens aberrations and vignetting in light field cameras

Cui¹,

Zhu²,

Gao³

2020

Opt. Express

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Light field cameras have been employed in myriad applications thanks to their 3D imaging capability. By placing a microlens array in front of a conventional camera, one can measure both the spatial and angular information of incoming light rays and reconstruct a depth map. The unique optical architecture of light field cameras poses new challenges on controlling aberrations and vignetting in lens design process. The results of our study show that field curvature can be numerically corrected for by digital refocusing, and vignetting must be minimized because it reduces the depth reconstruction accuracy. To address this unmet need, we herein present an optical design pipeline for light field cameras and demonstrated its implementation in a light field endoscope.

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Plenoptic Face Presentation Attack Detection

Cited by 5 publications

References 35 publications

A survey on face presentation attack detection mechanisms: hitherto and future perspectives

A survey on face presentation attack detection mechanisms: hitherto and future perspectives

A Dataset and Benchmark Towards Multi-Modal Face Anti-Spoofing Under Surveillance Scenarios

Developing an optical design pipeline for correcting lens aberrations and vignetting in light field cameras

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