The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper presents a novel automatic facial expressions recognition system (AFERS) using the deep network framework. The proposed AFERS consists of four steps: 1) geometric features extraction; 2) regional local binary pattern (LBP) features extraction; 3) fusion of both the features using autoencoders; and 4) classification using Kohonen self-organizing map (SOM)-based classifier. This paper makes...
The facial feature points localization is the core of face recognition, and its accuracy directly affects the accuracy of face recognition system. The accuracy of facial feature points is affected by light, noise, background, and face gestures. Considering the theoretical value and practical significance of facial feature points localization, this thesis goes into the most advanced algorithm of facial...
Discriminating probabilistic graphical models are reliable tools for a sequence labeling task. Conditional Random Fields (CRFs) are discriminative models which will enable us to label a sequence of input data. Other variations of CRFs have been proposed. Hidden Conditional Random Fields (HCRFs) incorporate hidden states to the CRF model and assign a label for the whole input sequence as the model's...
A novel and complete framework for face recognition with pose variations using only one image is proposed in this paper. Firstly, feature points on face images are located with view-based AAM (Active Appearance Model), based on which, alignment and normalization are operated on face images. Secondly, mapping from non-frontal images to frontal images is constructed based on the algorithm of linear...
As the world becomes more and more complex and so does the health problems faced by the individuals living on this Earth. Many of the health problems are hard to identify and explain. This is especially true with adolescents who are not able to speak at their early age of life and are not able to express the pain felt. There are also conditions with certain people who suffer from paralyses, strobe...
Human emotion recognition is an emerging research area in the field of social signal processing. Facial expression is an important means to detect human emotion. The problem is some facial expressions represent similar emotions. Thus, the recognition must consider the ambiguity in the way human expresses emotions through face. Existing methods do not take into account the level of expression's ambiguity...
Face recognition systems constitute a significant proportion of robotic systems. Learning algorithms such as deep learning and machine learning provide state-of-the-art algorithms with highly improved recognition rates. A majority of these algorithms convert a face image into a feature matrix, holistic or local, matched against all the feature matrixes in gallery for recognition. However, there is...
The recognition of an expression seems obvious and easy when classified by the human brain. However, it is clearly difficult for a computer to detect human face, extract all of the components characterizing the facial expression and then determine its classification from a single image. Moreover, based on videos, the process becomes even more complex because it must take simultaneously into account...
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...
In general human face has similar and different characteristics which play a very important role in recognizing facial expression. In this work, a new method presents to recognize different facial expressions from time sequential facial expression images. The performance of an automatic facial expression recognition system can be significantly improved by modeling the accuracy of various streams of...
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...
Detection of facial action units (AUs) is an important research field for recognizing emotional states in facial expressions. Here, we propose a novel, yet effective method, that utilizes variable decision thresholds at the prediction stage of a binary learning method for AU detection. The method performs a thresholding technique to find optimum values for each AU and make use of these thresholds...
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...
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...
Automated human facial image de-identification is a much needed technology for privacy-preserving social media and intelligent surveillance applications. Other than the usual face blurring techniques, in this work, we propose to achieve facial anonymity by slightly modifying existing facial images into "averaged faces" so that the corresponding identities are difficult to uncover. This approach...
E-Learning systems based on Affective computingare popularly used for emotional/behavioral analysis of the users. Emotions expressed by the user is depicted by detecting the facialexpression of the user and accordingly the teaching strategies willbe changed. The present eLearning systems mainly focus on thesingle user face detection. Hence, in this paper, we proposemultiuser face detection based eLearning...
Automatic facial expression recognition plays an important role in agent-based interface development and datadriven animation. This paper presents an intelligent facial action and emotion recognition system for a humanoid robot. Motivated by the Facial Action Coding System, this research focuses on the recognition of seven basic emotions and 18 Action Units (AU). Since effective facial representations...
In this paper we propose a component based face recognition method. In the framework, the facial landmarks is detected by using a view invariant AAM, and the components including eyes, nose, and mouth are extracted. To improve recognition rate, the components are aligned by using the procruetes analysis. After aligning, the component is insensitive to translation, scale, and rotation. The face features...
A solution to long distance outdoor face recognition is presented in this work. The proposed method, called the Two-Stage Alignment/Enhancement Filtering (TAEF) system, consists of three main components: a cross-distance face alignment technique, a cross-environment face enhancement technique, and a two-stage filtering system. Given a probe image, the procedure of face alignment, enhancement and matching...
Approach to construct 3D face model from an artist drawn sketch is an area of interest in image processing from last few decades. It has various application like police investigation, 3D cartoon modeling. From an individual's sketch it is possible to construct 3D face model using various techniques. To construct 3D face views, from the individuals sketch steps required are 2D landmark detection, 3D...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.