Face landmarking, defined as the detection and localization of certain characteristic points
on the face, is an important intermediary step for many subsequent face processing …

Computer science and biology have enjoyed a long and fruitful relationship for decades.
Biologists rely on computational methods to analyze and integrate large data sets, while …

Automatic affect analysis has attracted great interest in various contexts including the
recognition of action units and basic or non-basic emotions. In spite of major efforts, there …

Binary feature descriptors such as local binary patterns (LBP) and its variations have been
widely used in many face recognition systems due to their excellent robustness and strong …

This paper proposes a novel local feature descriptor, local directional number pattern (LDN),
for face analysis, ie, face and expression recognition. LDN encodes the directional …

This paper studies the influence of demographics on the performance of face recognition
algorithms. The recognition accuracies of six different face recognition algorithms (three …

Demographic estimation entails automatic estimation of age, gender and race of a person
from his face image, which has many potential applications ranging from forensics to social …

In this paper, we propose a context-aware local binary feature learning (CA-LBFL) method
for face recognition. Unlike existing learning-based local face descriptors such as …

We investigate the biologically inspired features (BIF) for human age estimation from faces.
As in previous bio-inspired models, a pyramid of Gabor filters are used at all positions of the …

Avoiding the use of complicated pre-processing steps such as accurate face and body part
segmentation or image normalization, this paper proposes a novel face/person image …