Book ChapterDOI
Face Spoofing Detection Using Dimensionality Reduced Local Directional Pattern and Deep Belief Networks
R. Srinivasa Perumal,G. G. Lakshmi Priya,P. V. S. S. R. Chandra Mouli +2 more
- Vol. 175, pp 330-338
TLDR
In this paper, a framework to detect whether a given face is spoofed face or not using dimensionality reduced local directional pattern descriptor (DR-LDP) combined with color textured features is presented.Abstract:
Face spoofing detection is considered a mandatory requirement for a robust face recognition system. This paper presents a framework to detect whether a given face is spoofed face or not using dimensionality reduced local directional pattern descriptor (DR-LDP) combined with color textured features. Deep Belief Networks (DBN) classifier has been used to classify the real faces and spoofed faces. The efficiency of our system elucidates performance by comparison of the results with the state-of-the-art method.read more
Citations
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Book ChapterDOI
Smart Attendance with Real Time Face Recognition
TL;DR: In this paper , a Smart Attendance with Real Time Face Recognition (SARTFR) is proposed based on Viola Jones Algorithm and LBP methods for student detection and recognition for tracking student attendance.
References
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Flexible, high performance convolutional neural networks for image classification
TL;DR: A fast, fully parameterizable GPU implementation of Convolutional Neural Network variants and their feature extractors are neither carefully designed nor pre-wired, but rather learned in a supervised way.
Journal ArticleDOI
Face Spoof Detection With Image Distortion Analysis
Di Wen,Hu Han,Anil K. Jain +2 more
TL;DR: An efficient and rather robust face spoof detection algorithm based on image distortion analysis (IDA) that outperforms the state-of-the-art methods in spoof detection and highlights the difficulty in separating genuine and spoof faces, especially in cross-database and cross-device scenarios.
Proceedings ArticleDOI
A face antispoofing database with diverse attacks
TL;DR: A face antispoofing database which covers a diverse range of potential attack variations, and a baseline algorithm is given for comparison, which explores the high frequency information in the facial region to determine the liveness.
Book ChapterDOI
Face liveness detection from a single image with sparse low rank bilinear discriminative model
TL;DR: This paper develops two new extensions to the sparse logistic regression model which allow quick and accurate spoof detection and proposes two strategies to extract the essential information about different surface properties of a live human face or a photograph, in terms of latent samples.