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Facial expression recognition is an important research domain in developing human-machine relations. This paper proposes a facial expression recognition system. This system is built using Constrained Local Models to fit the shapes on a face image and on Support Vector Machines (SVMs) to detect the face expressions. Different SVM architectures and trainings have been used including applying outliers...
This paper proposes a face recognition system that can be used to effectively match a face image scanned from an identity (ID) document against the face image stored in the bio-metric chip of such a document. The purpose of this specific face recognition algorithm is to aid the automatic detection of forged ID documents where the photography printed on the document's surface has been altered or replaced...
Facial expression recognition has become key challenge in the field of anthropomorphic human-computer interaction. In this paper, an approach is presented for facial expression recognition through the shape of facial feature points and the texture information of specific areas, based on Active Appearance Model (AAM). First, find out that the shape and texture parameters can express more personalized...
Emotion recognition systems have an important role to play in the human-computer interactive applications (HCI). These systems are using facial features of face images and they are verifying or identifying the emotions. In this study, emotion identification algorithms are improved by using just mouth region features of a face. Region of interest (mouth region) is detected by Viola-Jones algorithms...
Automatic discomfort detection for infants is important in health care, since infants have no ability to express their discomfort. In this paper, we propose an automatic system for detecting and monitoring discomfort of infants based on video analysis. The system is based on supervised learning and classifies previously unseen infants from the testing set in a fully automated way. Our system consists...
This paper presents an approach to blending a de-identified face region with its original background, for the purpose of completing the process of face de-identification. The re-identification risk of the de-identified FERET face images has been evaluated for the k-Diff-furthest face de-identification method, using several face recognition benchmark methods including PCA, LBP, HOG and LPQ. The experimental...
Detection and diagnosis of mental retardation in early stage is a problem for almost all Pediatric Doctors and Parents. The image database has been constructed by capturing face images of local normal and special persons and this work will help in early detection and diagnosis of Cognitive diseases. This paper focuses on implementation of Constrained Local Model (CLM) to classify the normal and special...
In this work, we exploit 3D Constrained Local Model (CLM) for facial landmark detection. Our approach integrates the geometric information of 3D face scans. The fast increase demand of 3D data invite to develop 3D image processing methods for many applications and especially for automatic landmark detection. The new step in this paper is the introduction of mesh histogram of gradients (meshHOG) as...
Breaking waves are very important phenomenon of the ocean surface, which play an important role in air-sea energy exchange. Waves break is a complex dynamic process. The process of breaking waves last three stages, which breaking waves shape are different. Through analysis of radar echo data, we know that whether the wave breaking occurred and even know that wave shape in which stage of wave breaking...
Non-contact measurement of cardiac pulse signals has attracted high interests due to its convenience and cost effectiveness. However, extracting pulse signals on mobile handheld devices (e.g. smartphones) based on face videos captured by mobile cameras usually suffers from low measurement accuracy due to misalignment errors in face tracking and inevitable illumination changes in a mobile scenario,...
Existing facial expression recognition (FER) algorithms aim to extract discriminative features from a face. These discriminative features can be extracted only from the informative regions of a face. In this view, several face models are proposed which are mainly intended to extract geometrical features from a face, and hence these models may not be suitable for extract discriminative texture features...
Face Recognition is one of the most popular and powerful method of identification of the Face Recognition Systems. The identification is very important to identify the Images, Video, Graphics and Blurred and Noisy Images, Video and Graphics. Face identification has received substantial attention from researchers in face recognition, pattern recognition, biometrics, computer vision, and communities...
In this paper we present a method for localisation of facial landmarks on human and sheep. We introduce a new feature extraction scheme called triplet-interpolated feature used at each iteration of the cascaded shape regression framework. It is able to extract features from similar semantic location given an estimated shape, even when head pose variations are large and the facial landmarks are very...
The application of correlation filters for the task of facial landmark detection has been studied by many vision works. Their success, however, is limited by the presence of large pose variations, expression and occlusion in face images. Moreover, existing correlation filters may suffer from poor discrimination to distinguish visually similar landmarks such as the right and left eyes. In this work,...
Facial fiducial detection is a challenging problem for several reasons like varying pose, appearance, expression, partial occlusion and others. In the past, several approaches like mixture of trees [32], regression based methods [8], exemplar based methods [7] have been proposed to tackle this challenge. In this paper, we propose an exemplar based approach to select the best solution from among outputs...
Face detection and tracking have wide applications, for example, law enforcement, gaming, image search, marketing, etc. The detection and tracking tasks are quite challenging. Tracking the face in an image includes gender identification and segmenting the face using the skin color. In the past, many methods have been proposed to identify a face in videos, such as feature-based detection, skin color...
Hurricanes generate massive amounts of marine debris in coastal waterways, causing environmental problems and hazards to safe navigation. Before debris can be removed, they must be located and identified, a tedious and time-consuming process. Automatic target recognition algorithms speed up this process by searching vast swaths of survey data to locate anomalies that could be debris. However, these...
This paper proposes a simple but efficient shape regression method for face alignment using an ensemble of random ferns. First, a classification method is used to obtain several mean shapes for initialization. Second, an ensemble of local random ferns is learned based on the correlation between the projected regression targets and local pixel-difference matrix for each landmark. Third, the ensemble...
Soft biometrics enable the identification of subjects based on semantic descriptions collected from eyewitnesses allowing people to search in surveillance databases. Although research has recently shown an increased interest in soft biometrics, not much of the work have used crowdsourcing, and it did not investigate the impact of feature selection on identification. In this paper, we introduce a new...
It is important to choose a good hairstyle for women because it can enhance their beauty, personality, and confidence. One of the most important factors to consider for choosing the right hairstyle is the individuals face shape. An effective face shape classification can be used for constructing a hairstyle recommendation system. This paper presents a classification approach that divides face shapes...
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