Face inversion hinders face processing in adults, while not affecting children in the same way. This fMRI study examines the neural underpinnings of the behavioral face inversion effect (FIE) from childhood to adulthood, and how face-selective regions in the brain may change with development. Adults, children, and teens performed a facial expression decision on upright and inverted face stimuli...

Automatic estimation of demographic attributes (e.g., age, gender, and race) from a face image is a topic of growing interest with many potential applications. Most prior work on this topic has used face images acquired under constrained and cooperative scenarios. This paper addresses the more challenging problem of automatic age, gender, and race estimation from real-life face images (face ima...

This paper proposes a novel image region descriptor for face recognition, named kernel Gabor-based weighted region covariance matrix (KGWRCM). As different parts are different effectual in characterizing and recognizing faces, we construct a weighting matrix by computing the similarity of each pixel within a face sample to emphasize features. We then incorporate the weighting matrices into a re...

We describe a virtual mirror interface which can react to people using robust, real-time face tracking. Our display can directly combine a user’s face with various graphical effects, performed only on the face region in the image. We have demonstrated our system in crowded environments with open and moving backgrounds. Robust performance is achieved using multi-modal integration, combining ster...

In this paper, an improved method to extract the chin contour under different face poses is proposed. Several previous approaches have used active contour models(ACM) or snakes in front-view facial images. However, successful chin contour extraction for a wide range of face poses has seldom been mentioned. An algorithm based on an improved snake for chin contour extraction is presented here and...

To achieve the problem of partial occlusion and multi-pose in the face detection, a face detection algorithm based on deep learning is proposed. Through establishing deep model, the probabilistic correlations of the visibilities are learned in different face local region. Firstly, face local regions are detected by part-based face detector. Secondly, the detection results are feed to deep model...

This paper describes the detection of faces in complex backgrounds where their sizes, positions and directions are arbitrary. We detect the faces by extracting face components such as eyes, a mouth and so on. We first extract face features and then calculate their likelihoods as each face component. Second we detect the face features which satisfy geometrical relations of the face. In order to ...

Visual scanpath recording was used to investigate the information processing strategies used by a prosopagnosic patient, SC, when viewing faces. Compared to controls, SC showed an aberrant pattern of scanning, directing attention away from the internal configuration of facial features (eyes, nose) towards peripheral regions (hair, forehead) of the face. The results suggest that SC's face recogn...

In this paper we present a widespread and significant survey of face detection algorithms. Face detection is a necessary first-step in face recognition systems, with the idea of localizing and extracting the face region from the background. It also has numerous applications in areas such as passport-verification, video conferencing, crowd surveillance, detective agencies and military purposes. ...

In this paper, we introduce the Face Magnifier Network (Face-MageNet), a face detector based on the Faster-RCNN framework which enables the flow of discriminative information of small scale faces to the classifier without any skip or residual connections. To achieve this, Face-MagNet deploys a set of ConvTranspose, also known as deconvolution, layers in the Region Proposal Network (RPN) and ano...