As the individual identification, access control and security appliance issues attract much attention, face recognition applications are more and more popular. The challenge of face recognition is that the performance is mainly constrained by the variations of illumination, expression, pose and accessory. And most algorithms which were proposed in recent years focused on how to conquest these c...

Face verification for unrestricted faces in the wild is a challenging task. This paper proposes a method based on two deep convolutional neural networks (CNN) for face verification. In this work, we explore using identification signals to supervise one CNN and the combination of semi-verification and identification to train the other one. In order to estimate semi-verification loss at a low com...

In many real-world applications such as smart card solutions, law enforcement, surveillance and access control, the limited training sample size is the most fundamental problem. By making use of the low-rank structural information of the reconstructed error image, the so-called nuclear norm-based matrix regression has been demonstrated to be effective for robust face recognition with continuous...

This paper proposes a novel face recognition methodology, which is based on the combination of the texture operator, namely Multi-scale Local Binary Pattern (MSLBP), face image filtering and discriminative feature weighting algorithms. Presented MSLBP principle enhances the discriminative power of the original Local Binary Pattern operator. The combination of the MSLBP and low-pass filtering im...

This paper introduces the establishment of PolyU near-infrared face database (PolyU-NIRFD) and presents a new coding scheme for face recognition. The PolyU-NIRFD contains images from 350 subjects, each contributing about 100 samples with variations of pose, expression, focus, scale, time, etc. In total, 35,000 samples were collected in the database. The PolyU-NIRFD provides a platform for resea...

A method for the adaptation of a generic 3-D face model to an actual face in a head-and-shoulders scene is discussed, with application to video-telephony. The adaptation is carried out both on a global scale to reposition and resize the wireframe, as well as on a local scale to mimic individual physiognomy. To this effect a hierarchical scheme is developed to extract the semantic features in th...

this study has investigated smallholder farmers’ household food security level in mazandaran province during the two times i.e pre-harvest period and post-harvest period. using krejcie and morgan’s detrmining sample table, 384 farmers selected as a sample. a multi-stage sampling technique was used to select preciously subjects. household food insecurity access scale (hfias) was the main tool fo...

Due to largely mounting of photo sharing in social network services, there is a strong need for large scale content-based face image retrieval which is enabling device for many emerging applications. It is very exigent to find a human face image from large scale database which might hold huge amount of face images of people. Existing methods regulate the location and illumination differences be...

Face detection is a fundamental problem in computer vision. It is still a challenging task in unconstrained conditions due to significant variations in scale, pose, expressions, and occlusion. In this paper, we propose a multi-branch fully convolutional network (MB-FCN) for face detection, which considers both efficiency and effectiveness in the design process. Our MB-FCN detector can deal with...