Face detection is one of the challenging problems in the image processing. The basic aim of face detection is determine if there is any face in an image. And then locate position of a face in image. Human face detected in an image can represent the presence of a human in a place. Evidently, face detection is the first step towards creating an automated system, which may involve other face proce...

This paper focuses on the problem of generating human face pictures from specific attributes. The existing CNN-based face generation models, however, either ignore the identity of the generated face or fail to preserve the identity of the reference face image. Here we address this problem from the view of optimization, and suggest an optimization model to generate human face with the given attr...

This paper proposes a novel image preprocessing technique based on binary patterns for illumination invariant face recognition. The face recognition system comprised of a centralized gradient pattern image and facial features based on image covariance. The centralized gradient pattern image is obtained by AND operation of a modified local binary pattern image and a modified local directional pa...

Automatic face detection in images is a very popular application that makes good use of image processing techniques (and also some pattern classification methods) and it is useful for many real-life imaging automations such as face identification for biometric authentication, surveillance of human activity, image retrieval and image classification. In color images, face detection may have an ad...

The authors explore the possibilities of a dense model-free three-dimensional (3D) face reconstruction method, based on image sequences from a single camera, to improve the current state of forensic face comparison. They propose a new model-free 3D reconstruction method for faces, based on the Lambertian reflectance model to estimate the albedo and to refine the 3D shape of the face. This metho...

Face hallucination refers to inferring an High-Resolution (HR) face image from the input Low-Resolution (LR) one. It plays a vital role in LR face recognition by both manual and computer. The eigentransformation method based on Principal Component Analysis (PCA), which represents face image as a linear combination of the eigenfaces, has attracted considerable interests because of its simplicity...

Face recognition presents a challenging problem in the field of image analysis and computer vision. The security of information is becoming very significant and difficult. Security cameras are presently common in airports, Offices, University, ATM, Bank and in any locations with a security system. Face recognition is a biometric system used to identify or verify a person from a digital image. F...

Recent years have witnessed great progress in image deblurring. However, as an important application case, the deblurring of face images has not been well studied. Most existing face deblurring methods rely on exemplar set construction and candidate matching, which not only cost much computation time but also are vulnerable to possible complex or exaggerated face variations. To address the afor...

In Fig. 2–Fig. 14, we present additional comparisons to the current state-of-art singleimage methods for face modeling [2] and intrinsic image decomposition [1]. We show results with white illumination in Fig. 2–Fig. 7 and non-white illumination in Fig. 8– Fig. 14. Note the differences in decomposed albedo maps between the Caucasian woman in Fig. 13 and the black woman in Fig. 14 under the same...

Human face plays an important role in our social interaction, conveying people’s identity but it is a dynamic object and has a high degree of variability in its appearences.So to overcome this variability Face Detection and face recognition methods have been introduced. Face detection is the basic step of face recognition. In this paper, we present a comprehensive and critical survey of face de...