The performance of a biometric system that relies on a single biometric modality (eg,
fingerprints only) is often stymied by various factors such as poor data quality or limited …

Biometric recognition technology has made significant advances over the last decade and is
now used across a number of services and applications. However, this widespread …

Systems incorporating biometric technologies have become ubiquitous in personal,
commercial, and governmental identity management applications. Both cooperative (eg …

Recent research has established the possibility of deducing soft-biometric attributes such as
age, gender, and race from an individual's face image with high accuracy. However, this …

Deep neural network (DNN) architecture based models have high expressive power and
learning capacity. However, they are essentially a black box method since it is not easy to …

The tremendous progress in deep learning has enabled to extract soft-biometric attributes
from faces, which raises privacy concerns over images collected for face recognition …

The concerns on visual privacy have been increasingly raised along with the dramatic
growth in image and video capture and sharing. Meanwhile, with the recent breakthrough in …

Face de-identification (De-ID) removes face identity information in face images to avoid
personal privacy leakage. Existing face De-ID breaks the raw identity by cutting out the face …

Facial attribute analysis has received considerable attention when deep learning techniques
made remarkable breakthroughs in this field over the past few years. Deep learning based …

With the popularity of using computer vision technology in monitoring system, there is an
increasing societal concern on intruding people's privacy as the captured images/videos …