Attention-Based Spatial-Temporal Multi-Scale Network for Face Anti-Spoofing

Zheng, Wei; Yue, Mengyuan; Zhao, Shuhuan; Liu, Shuaiqi

doi:10.1109/tbiom.2021.3066983

Cited by 27 publications

(17 citation statements)

References 52 publications

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“…The method can be deceived with video replay attack. Zheng et al [8] combined depth and multi scale features to detect face spoofing. Higher level feature representation of depth and multi scale is learnt using a two steam spatial temporal network.…”

Section: Related Workmentioning

confidence: 99%

“…Cai et al [7] Colour and meta features are used to detect face liveliness Fails for video replay attack Zheng et al [8] combined depth and multi scale features to detect face spoofing Fails for video replay attack Song et al [9] face spoof detection method based on depth cue The approach can be deceived presenting two different images in quick succession matching the acquisition order.…”

Section: A Liveliness Detectionmentioning

confidence: 99%

“…The dataset has 990 real face videos, 3,960 fake face videos. The performance of the proposed solution is compared against attention based solution proposed by Zheng et al (2021) [8] and spatial gradient solution proposed by Wang et al (2020) [17]. Though the work [8] and [17] were tested for number of datasets, in this work we restrict the comparison to OULU-NPU dataset alone.…”

Section: A Liveliness Detectionmentioning

confidence: 99%

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Challenge Responsive Multi Modal Biometric Authentication Resilient to Presentation Attacks

2022

IJIES

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Multimodal biometric systems are a natural evolution of traditional biometric authentication systems with use of multiple biometric to enhance the security level. Presentation attacks in form of photos and replay videos are becoming a threat to the biometric authentication systems and it becomes necessary to prevent from these attacks for an enhanced security level. This work proposes a challenge response based multi modal biometric authentication resilient to presentation attack. The proposed system is designed for multi modal biometric involving face and iris biometrics with challenge in form of arbitrary emotion invoking image at a random position on the screen. The changes in region of interest around the Facial landmarks and distance of iris to Facial landmarks are captured as response. The response is then matched with expected response derived based on the position of arbitrary emotion invoking image on screen to detect presentation attacks. In addition the work also proposes a hybrid deep feature which provides an addition security in recognition process to ensure authentication failure for fake samples. The error rate in leakage of spoofs is very low in proposed solution (less than 1%) in different environments compared to existing works. The recognition accuracy of face is atleast 1% higher and atleast 2% higher for IRIS in proposed solution compared to existing works.

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Section: Related Workmentioning

confidence: 99%

Section: A Liveliness Detectionmentioning

confidence: 99%

Section: A Liveliness Detectionmentioning

confidence: 99%

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Challenge Responsive Multi Modal Biometric Authentication Resilient to Presentation Attacks

2022

IJIES

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“…One of the factors that contributes to its popularity is the extensive use of surveillance cameras in various applications [ 9 ]. In the past two decades, numerous face recognition methods have been developed to recognize a person for various purposes, such as criminal detection, law enforcement, image spoofing, and other security applications [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. The pioneer of face recognition utilizes either the visible light images or infrared images to identify a person [ 10 , 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

“…The recognition of these two types of images is done in the same spectral band. In addition, some efforts to apply deep learning in face image recognition have been demonstrated in [ 14 , 15 , 16 , 17 ]. These works also considered the recognition between images in the same spectral band, i.e., the visible images and their various versions.…”

Section: Introductionmentioning

confidence: 99%

Homomorphic Filtering and Phase-Based Matching for Cross-Spectral Cross-Distance Face Recognition

Arnia

Oktiana

Saddami

et al. 2021

Sensors

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Facial recognition has a significant application for security, especially in surveillance technologies. In surveillance systems, recognizing faces captured far away from the camera under various lighting conditions, such as in the daytime and nighttime, is a challenging task. A system capable of recognizing face images in both daytime and nighttime and at various distances is called Cross-Spectral Cross Distance (CSCD) face recognition. In this paper, we proposed a phase-based CSCD face recognition approach. We employed Homomorphic filtering as photometric normalization and Band Limited Phase Only Correlation (BLPOC) for image matching. Different from the state-of-the-art methods, we directly utilized the phase component from an image, without the need for a feature extraction process. The experiment was conducted using the Long-Distance Heterogeneous Face Database (LDHF-DB). The proposed method was evaluated in three scenarios: (i) cross-spectral face verification at 1m, (ii) cross-spectral face verification at 60m, and (iii) cross-spectral face verification where the probe images (near-infrared (NIR) face images) were captured at 1m and the gallery data (face images) was captured at 60 m. The proposed CSCD method resulted in the best recognition performance among the CSCD baseline approaches, with an Equal Error Rate (EER) of 5.34% and a Genuine Acceptance Rate (GAR) of 93%.

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Intensity-Chromaticity-Luminance (ICL) Based Technique for Face Spoofing Detection

Karthika,

Padmavathi

2024

Communications in Computer and Information Science

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Attention-Based Spatial-Temporal Multi-Scale Network for Face Anti-Spoofing

Cited by 27 publications

References 52 publications

Challenge Responsive Multi Modal Biometric Authentication Resilient to Presentation Attacks

Challenge Responsive Multi Modal Biometric Authentication Resilient to Presentation Attacks

Homomorphic Filtering and Phase-Based Matching for Cross-Spectral Cross-Distance Face Recognition

Intensity-Chromaticity-Luminance (ICL) Based Technique for Face Spoofing Detection

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