Appearance Of Human Face Research Articles

A Mobile Surveillance System with Face Detection and Recognition Abilities

This paper proposes a mobile surveillance system similar to an electronic dog which has the ability to move around a certain location all while detecting and recognizing the individuals and notifying the respective authorities about the detected person. The system uses an Arduino UNO microcontroller along with IR receiver and remote to function as a remote-controlled vehicle while also providing an option for automatic movement of the vehicle. The system also has an integrated camera that constantly feeds live video to a computer system. Haar-cascades take in the frames of videos and detect appearance of human face. Then, pretrained FaceNet Convolutional Neural Network (CNN) compares the detected face to the authorized faces in an attempt to recognize the face. The system also boasts the feature of email notification for which it employs the SMTP protocol to send an email with the detected face to the authorized personnel. The methods and techniques used to implement these features are presented in depth in this paper.

Joint Demographic Features Extraction for Gender, Age and Race Classification based on CNN

Automatic verification and identification of face from facial image to obtain good accuracy with huge dataset of training and testing to using face attributes from images is still challengeable. Hence proposing efficient and accurate facial image identification and classification based of facial attributes is important task. The prediction from human face image is much complex. The proposed research work for automatic gender, age and race classification is based on facial features and Convolutional Neural Network (CNN). The proposed study uses the physical appearance of human face to predict age, gender and race. The proposed methodology consists of three sub systems, Gender, Ageing and Race. Therefore different feature are extracted for every sub system. These features are extracted by using Primary, Secondary features, Face Angle, Wrinkle Analysis, LBP and WLD. The accuracy of classification is based on these features. CNN used to classify by using these features. The proposed study has been evaluated and tested on large database MORPH II and UTKF. The performance of proposed system is compared with state of art techniques.

Design and Implementation of Resampling Techniques for Face Recognition using Classical LDA Algorithm in MATLAB

A number of applications require robust human face recognition under varying environmental lighting conditions and different facial expressions, which considerably vary the appearance of human face. However, in many face recognition applications, only a small number of training samples for each subject are available; these samples are not able to capture all the facial appearance variations, to utilize the resampling techniques to generate several subsets of samples from the original training dataset. A classic appearance-based recognizer, LDA-based classifier, is applied to each of the generated subsets to construct a LDA representation for face recognition. The discrimination power of various human facial features is studied and a new scheme for automatic face recognition (AFR) is proposed. This paper focuses on the linear discriminant analysis (LDA) of different aspects of human faces in the spatial as well as in the wavelet domain. The LDA of faces also provides us with a small set of features that carry the most relevant information for classification purposes. The features are obtained through eigenvector analysis of scatter matrices with the objective of maximizing between-class variations and minimizing within-class variations. The result is an efficient projection-based feature-extraction and classification scheme for AFR. Multisource data analysis are used to provide more reliable recognition results. For a medium-sized database of human faces, excellent classification accuracy is achieved with the use of very-lowdimensional feature vectors. Moreover, the method is applicable to many other image-recognition tasks.

Neurologic Manifestations in Sagliker Syndrome: Uglifying Human Face Appearance in Severe and Late Secondary Hyperparathyroidism in Chronic Renal Failure Patients

Patients with chronic renal failure (CRF) often have signs and symptoms related to fluid and electrolyte disturbances, anemia, malnutrition, bone disease, and gastrointestinal problems. Vascular and neurologic impairment in particular remain an important source of morbidity and mortality in this vulnerable patient population. Sagliker syndrome is a novel syndrome that was recently described in 2004 in patients with CRF and severe and late secondary hyperparathyroidism who suffered from severe skull and facial bone changes, particularly from uglifying human face appearances and neuropsychiatric disorders. The goal of this study was to assess neuropsychiatric manifestations occurring in CRF patients with Sagliker syndrome. Four female and 8 male patients with CRF on regular dialysis at the hemodialysis units of the Internal Medicine Departments around southern Turkey participated in the study. All patients underwent a clinical neurologic examination performed by the same neurologist. Neuropsychiatric signs and symptoms were found in all cases. The results showed that the most frequent neurologic manifestations in CRF patients with Sagliker syndrome were headache, polyneuropathy, cranial neuropathy, fatigue, and psychiatric disorders.

Cephalometric Evaluation of Patients With Sagliker Syndrome: Uglifying Human Face Appearance in Severe and Late Secondary Hyperparathyroidism in Chronic Renal Failure Patients

It is well known that secondary hyperparathyroidism may be an extremely severe condition in chronic renal failure, and almost all patients with chronic kidney disease, even in the well-developed countries, encounter every kind of bone abnormalities if they are not treated properly. Although some sporadic cases have been reported of unique facial bone changes, the largest collection of this phenomenon has been reported by Sagliker et al. We also have found 6 of 9 patients who have these changes (Sagliker syndrome) to manifest class II malocclusion of the upper and lower jaws according to dental universally accepted criteria by performing cephalometric studies, x-ray plain films, tomographic procedures, and drawing technology.

Active differential CMOS imaging device for human face recognition

This letter describes an original CMOS imaging system dedicated to human face recognition. The main interest of this work is to provide ambient light invariant images and facilitate segmentation of the face from the background. This system has been implemented in a specially designed CMOS smart image sensor with only one analog memory per pixel. This simple pixel design gives the possibility to incorporate this functionality into classic low-cost CMOS image sensors. One of its possible applications is face recognition, since the human face appearance is dramatically dependent on illumination conditions. A first indoor experience with different illumination conditions shows that a simple correlation-based verification algorithm on face images of 25 people of the INT database gives promising results.

Sagliker syndrome: Uglifying human face appearance in late and severe secondary hyperparathyroidism in chronic renal failure

Almost every patient with chronic renal failure (CRF) eventually develops secondary hyperparathyroidism (SH) unless they are treated with proper and novel medications in advanced medical centers by skilled medical personnel. Every kind of bone abnormality including skull deformities has been described in detail by almost every concerned researcher and textbook, but descriptions of this phenomenon are limited in the medical literature to the years from 1973 to 1977. To our knowledge, extensive data regarding uglifying human face appearances have not been defined so far in the literature. We are therefore making this addition to the clinical nephrology field by accumulating such data. After we found 2 consecutive peculiar and unique patients with uglifying human face appearances in 2000, we attempted to inform and draw attention to this new entity to all hemodialysis (HD) centers in Turkey, as well as in other developing countries around the world to collect data on this phenomenon. Accordingly, we visited dialysis centers and patients' houses to collect detailed information, including medical clinical histories, physical examinations, laboratory data, biographies, current medications, and so forth. We found 25 patients who had CRF, SH, short stature, extremely severe skull changes, maxillary and mandibular bone changes, teeth/dental abnormalities, and soft and innocuous tumoral tissues in the mouth (hence, uglifying the appearance of the face), fingertip changes, severe psychologic problems, and depression. It appears that patients with CRF may have a new syndrome of bone deformities that have long been neglected, ignored, and forgotten since the mid-1970s when they were first described. This is vital and critical information for the clinical status of patients who suffered from the syndrome that we have named Sagliker syndrome (SS), and we believe there are many more patients in the world who are suffering from it.