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Anjith George
Researcher at Idiap Research Institute
Publications - 48
Citations - 1462
Anjith George is an academic researcher from Idiap Research Institute. The author has contributed to research in topics: Facial recognition system & Eye tracking. The author has an hindex of 16, co-authored 43 publications receiving 878 citations. Previous affiliations of Anjith George include Indian Institute of Technology Kharagpur.
Papers
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Proceedings ArticleDOI
Deep Pixel-wise Binary Supervision for Face Presentation Attack Detection
Anjith George,Sébastien Marcel +1 more
TL;DR: A Convolutional Neural Network (CNN) based framework for presentation attack detection, with deep pixel-wise supervision, suitable for deployment in smart devices with minimal computational and time overhead is introduced.
Journal ArticleDOI
Biometric Face Presentation Attack Detection With Multi-Channel Convolutional Neural Network
Anjith George,Zohreh Mostaani,David Geissenbuhler,Olegs Nikisins,André Anjos,Sébastien Marcel +5 more
TL;DR: In this article, a multi-channel Convolutional Neural Network-based approach for presentation attack detection (PAD) has been proposed, and the new Wide Multi-Channel presentation Attack (WMCA) database is introduced.
Journal ArticleDOI
A Vision-Based System for Monitoring the Loss of Attention in Automotive Drivers
TL;DR: A robust real-time embedded platform to monitor the loss of attention of the driver during day and night driving conditions using the percentage of eye closure to indicate the alertness level is proposed.
Proceedings ArticleDOI
A real time facial expression classification system using Local Binary Patterns
TL;DR: In this paper, a facial expression classification algorithm is proposed which uses Haar classifier for face detection purpose, Local Binary Patterns(LBP) histogram of different block sizes of a face image as feature vectors and classifies various facial expressions using Principal Component Analysis (PCA).
Proceedings ArticleDOI
A Real Time Facial Expression Classification System Using Local Binary Patterns
TL;DR: A facial expression classification algorithm is proposed which uses Haar classifier for face detection purpose, Local Binary Patterns histogram of different block sizes of a face image as feature vectors and classifies various facial expressions using Principal Component Analysis (PCA).