An Improved Algorithm for Eye Corner Detection

In this paper, a modified algorithm for the detection of nasal and temporal eye corners is presented. The algorithm is a modification of the Santos and Proenka Method. In the first step, we detect the face and the eyes using classifiers based on Haar-like features. We then segment out the sclera, from the detected eye region. From the segmented sclera, we segment out an approximate eyelid contour. Eye corner candidates are obtained using Harris and Stephens corner detector. We introduce a post-pruning of the Eye corner candidates to locate the eye corners, finally. The algorithm has been tested on Yale, JAFFE databases as well as our created database

Trigeminal neuralgia - diagnosis and treatment

Introduction Trigeminal neuralgia (TN) is characterized by touch-evoked unilateral brief shock-like paroxysmal pain in one or more divisions of the trigeminal nerve. In addition to the paroxysmal pain, some patients also have continuous pain. TN is divided into classical TN (CTN) and secondary TN (STN). Etiology and pathophysiology Demyelination of primary sensory trigeminal afferents in the root entry zone is the predominant pathophysiological mechanism. Most likely, demyelination paves the way for generation of ectopic impulses and ephaptic crosstalk. In a significant proportion of the patients, the demyelination is caused by a neurovascular conflict with morphological changes such as compression of the trigeminal root. However, there are also other unknown etiological factors, as only half of the CTN patients have morphological changes. STN is caused by multiple sclerosis or a space-occupying lesion affecting the trigeminal nerve. Differential diagnosis and treatment Important differential diagnoses include trigeminal autonomic cephalalgias, posttraumatic or postherpetic pain and other facial pains. First line treatment is prophylactic medication with sodium channel blockers, and second line treatment is neurosurgical intervention. Future perspectives Future studies should focus on genetics, unexplored etiological factors, sensory function, the neurosurgical outcome and complications, combination and neuromodulation treatment as well as development of new drugs with better tolerability

An Approach to Detect the Region of Interest of Expressive Face Images

AbstractOn human face, non-rigid facial movements due to facial expressions cause noticeable alterations in their usual shapes, which sometimes create occlusions in facial feature areas making face recognition as a difficult problem. The paper presents an automatic Region of Interest (ROI) detection technique of six universal expressive face images. The proposed technique is a facial geometric based hybrid approach. The localization accuracy was evaluated by rectangular error measure and was tested on Japanese Female Facial Expression (JAFFE) database. The average localization accuracy of all detected facial regions is 94%

Face pose estimation in monocular images

People use orientation of their faces to convey rich, inter-personal information. For example, a person will direct his face to indicate who the intended target of the conversation is. Similarly in a conversation, face orientation is a non-verbal cue to listener when to switch role and start speaking, and a nod indicates that a person has understands, or agrees with, what is being said. Further more, face pose estimation plays an important role in human-computer interaction, virtual reality applications, human behaviour analysis, pose-independent face recognition, driver s vigilance assessment, gaze estimation, etc. Robust face recognition has been a focus of research in computer vision community for more than two decades. Although substantial research has been done and numerous methods have been proposed for face recognition, there remain challenges in this field. One of these is face recognition under varying poses and that is why face pose estimation is still an important research area. In computer vision, face pose estimation is the process of inferring the face orientation from digital imagery. It requires a serious of image processing steps to transform a pixel-based representation of a human face into a high-level concept of direction. An ideal face pose estimator should be invariant to a variety of image-changing factors such as camera distortion, lighting condition, skin colour, projective geometry, facial hairs, facial expressions, presence of accessories like glasses and hats, etc. Face pose estimation has been a focus of research for about two decades and numerous research contributions have been presented in this field. Face pose estimation techniques in literature have still some shortcomings and limitations in terms of accuracy, applicability to monocular images, being autonomous, identity and lighting variations, image resolution variations, range of face motion, computational expense, presence of facial hairs, presence of accessories like glasses and hats, etc. These shortcomings of existing face pose estimation techniques motivated the research work presented in this thesis. The main focus of this research is to design and develop novel face pose estimation algorithms that improve automatic face pose estimation in terms of processing time, computational expense, and invariance to different conditions

Diagnostics Of Supernumerary Teeth In Orthodontic Relapse

Aim: increasing the effectiveness of diagnosis and further orthodontic-surgical treatment of various clinical forms of hyperdontia (supernumerary teeth) and preventing recurrence with the use of cone-ray computer tomography data in orthodontic practice.Materials and methods. The clinical case of patient (born in 2004) treatment is presented, with severe hyperdontia and retention of teeth that had little effect on the formation of the general configuration of occlusion. The patient's examination and treatment was carried out with the assistance of clinical, anthropometric and radiological data. The clinical method was to examine the patient and formulate a plan for further orthodontic therapy. The radiological method consisted of data analysis of cefalometry by Bjork, Steiner using a computer program and conducting a survey using a cone-ray computer tomography, followed by the use of these data in diagnosis and orthodontic treatment.Results. Following the clinical and radiological methods of examination and subsequent orthodontic surgery, the corresponding end results were obtained:1. The localization and topography of supernumerary teeth as the causes of relapse of pathology with the help of data obtained with the help of CBCT.2. Radiographic picture reflected on the sagital and axial re-formats of tomograms for the diagnosis of supernumerary teeth, is more informative than diagnostics by standard diagnostic protocols.3. After analysis of the study data, a more meaningful protocol of surgical intervention is prescribed.4. Implementation of the results of modern diagnostics significantly influenced on the final result of orthodontic treatment.Conclusions. Thus, in the process of corresponding work installed:– the availability of computer tomography data is crucial for objective and qualitative diagnosis and treatment of hypertension.– the general level of diagnostics during the intervention is significantly increased