Data-Fusion-Based Two-Stage Cascade Framework for Multimodality Face Anti-Spoofing

Anti-spoofing, Face

A Distributed Face Recognition Framework Based on Data Fusion

To accomplish face recognition more efficiently, a distributed face recognition framework based on MB-LBP features and data fusion is presented in this paper. Firstly, four face regions are interactively marked and the Multi-scale Block Local Binary Patterns are extracted from these regions to achieve both locally and globally informative features. Secondly, a distributed framework is introduce...

Learn Convolutional Neural Network for Face Anti-Spoofing

Though having achieved some progresses, the hand-crafted texture features, e.g., LBP [23], LBP-TOP [11] are still unable to capture the most discriminative cues between genuine and fake faces. In this paper, instead of designing feature by ourselves, we rely on the deep convolutional neural network (CNN) to learn features of high discriminative ability in a supervised manner. Combined with some...

A Method of Detections’ Fusion for GNSS Anti-Spoofing

The spoofing attack is one of the security threats of systems depending on the Global Navigation Satellite System (GNSS). There have been many GNSS spoofing detection methods, and each of them focuses on a characteristic of the GNSS signal or a measurement that the receiver has obtained. The method based on a single detector is insufficient against spoofing attacks in some scenarios. How to fus...

An Efficient Face Spoofing Detection Technique for Big Data

Big data refers to huge information whose quantity is beyond the capacity of the system to manage, process and capture. On the basis of the biological and behavioral characteristics of the human, information gathered from which person can be recognized and referred as biometrics. Example includes finger print, face, voice and behavioral analysis etc. Among these, face recognition will not make ...