502 research outputs found
A Review on Face Anti-Spoofing
The biometric system is a security technology that uses information based on a living person's characteristics to verify or recognize the identity, such as facial recognition. Face recognition has numerous applications in the real world, such as access control and surveillance. But face recognition has a security issue of spoofing. A face anti-spoofing, a task to prevent fake authorization by breaching the face recognition systems using a photo, video, mask, or a different substitute for an authorized person's face, is used to overcome this challenge. There is also increasing research of new datasets by providing new types of attack or diversity to reach a better generalization. This paper review of the recent development includes a general understanding of face spoofing, anti-spoofing methods, and the latest development to solve the problem against various spoof types
Recent Advancement in 3D Biometrics using Monocular Camera
Recent literature has witnessed significant interest towards 3D biometrics
employing monocular vision for robust authentication methods. Motivated by
this, in this work we seek to provide insight on recent development in the area
of 3D biometrics employing monocular vision. We present the similarity and
dissimilarity of 3D monocular biometrics and classical biometrics, listing the
strengths and challenges. Further, we provide an overview of recent techniques
in 3D biometrics with monocular vision, as well as application systems adopted
by the industry. Finally, we discuss open research problems in this area of
researchComment: Accepted and presented in IJCB 202
Anti-Spoofing Using Transfer Learning with Variational Information Bottleneck
Recent advances in sophisticated synthetic speech generated from
text-to-speech (TTS) or voice conversion (VC) systems cause threats to the
existing automatic speaker verification (ASV) systems. Since such synthetic
speech is generated from diverse algorithms, generalization ability with using
limited training data is indispensable for a robust anti-spoofing system. In
this work, we propose a transfer learning scheme based on the wav2vec 2.0
pretrained model with variational information bottleneck (VIB) for speech
anti-spoofing task. Evaluation on the ASVspoof 2019 logical access (LA)
database shows that our method improves the performance of distinguishing
unseen spoofed and genuine speech, outperforming current state-of-the-art
anti-spoofing systems. Furthermore, we show that the proposed system improves
performance in low-resource and cross-dataset settings of anti-spoofing task
significantly, demonstrating that our system is also robust in terms of data
size and data distribution.Comment: Submitted to Interspeech 202
Time-Domain Based Embeddings for Spoofed Audio Representation
Anti-spoofing is the task of speech authentication. That is, identifying
genuine human speech compared to spoofed speech. The main focus of this paper
is to suggest new representations for genuine and spoofed speech, based on the
probability mass function (PMF) estimation of the audio waveforms' amplitude.
We introduce a new feature extraction method for speech audio signals: unlike
traditional methods, our method is based on direct processing of time-domain
audio samples. The PMF is utilized by designing a feature extractor based on
different PMF distances and similarity measures. As an additional step, we used
filter-bank preprocessing, which significantly affects the discriminative
characteristics of the features and facilitates convenient visualization of
possible clustering of spoofing attacks. Furthermore, we use diffusion maps to
reveal the underlying manifold on which the data lies.
The suggested embeddings allow the use of simple linear separators to achieve
decent performance. In addition, we present a convenient way to visualize the
data, which helps to assess the efficiency of different spoofing techniques.
The experimental results show the potential of using multi-channel PMF based
features for the anti-spoofing task, in addition to the benefits of using
diffusion maps both as an analysis tool and as an embedding tool
- …