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A human can read the other party's emotion through his/her face, and an eye is the most important factor to deliver emotion. By extracting eyes from a person in a picture, and applying them to a character, the character having eyes suitable for a video direction situation can be created, and emotion can be effectively delivered. This study suggested a system that can create fairy tale's characters...
In this paper we present a novel approach for 3D facial expression recognition based on a registration method. The used registration method, called the Coherent Point Drift (CPD), is applied to estimate complex non-linear and nonrigid transformation between 3D facial surfaces. The computed transformation allows to recover shape deformations that are induced by facial expression variations. Machine...
Face Feature Point Detection (FFPD) is a significant and interesting topic in many related areas of face recognition. A new face mesh model is presented in this paper to realize the FFPD in a fast and training-free approach. At first, an automatic face mesh initialization algorithm based on the detection of face, eye-pairs and mouth is proposed. Second, a local operator referred as Edge Attractor...
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...
In this paper, we present a new radial string representation and matching approach for 3D face recognition under expression variations and partial occlusions. The radial strings are an indexed collection of strings emanating from the nose tip of a face scan. The matching between two radial strings is conducted through a dynamic programming process, in which a partial matching mechanism is established...
Dealing with a reliable face-ageing model has been an interesting topic with many envisioned applications such as those are related to investigation and forensics. Contrary to most previous works which deal with predictive face models, in this work, we propose a model that can estimate one’s appearance in his youth down to it being in the age of 3-4 years. In this proposed approach, the youth face...
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...
In order to enhance the facial recognition rate of the SIFT, the improved SIFT fused with shape model was proposed and applied to face recognition. Firstly the shape model was established by utilizing the training process of AAM model, and was used to get the initial positions of facial feature points, then the feature descriptors of SIFT which have a nearest Euclidean distance with the initial positions...
This article presents two facial geometric-based approaches for facial expression recognition using support vector machines. The first method performed an experimental research to identify the relevant geometric features for human point of view and achieved 85% of recognition rate. The second experiment employed the Correlation Feature Selection and achieved 96.11% of recognition rate. All experiments...
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 point detection in real-world conditions presents large variations in shapes and occlusions due to differences in poses, expressions, use of accessories, which may lead to a large difficultly in locating facial points. In this paper, we propose a regression-based sparse coding method for facial point detection. The method combines the regression-based concept with sparse reconstruction methods...
In modern days the demand for biometrics increases rapidly. The world still needs to solve many problems and answer to lot of questions regarding to biometrics for creating better solutions for recognition and verification of objects. Biometrics has become really important topic of our security. Number of input samples per person affects recognition in modern algorithms used for face recognition....
Gender recognition from face images is an important application in the fields of security, retail advertising and marketing. We propose a novel descriptor based on COSFIRE filters for gender recognition. A COSFIRE filter is trainable, in that its selectivity is determined in an automatic configuration process that analyses a given prototype pattern of interest. We demonstrate the effectiveness of...
Head detection may be more demanding than face recognition and pedestrian detection in the scenarios where a face turns away or body parts are occluded in the view of a sensor, but locating people is needed. In this paper, we introduce an efficient head detection approach for single depth images at low computational expense. First, a novel head descriptor is developed and used to classify pixels as...
In this study, we present a new approach to the problem of face classification, which relies on the linguistic description of the facial features. In this method, face descriptors are represented through the Analytic Hierarchy Process (AHP) and formalized as information granules. Moreover, neural networks are used to construct efficient classifiers. Furthermore, with usage of AHP we realize a transition...
Expressions are commonly presented through the motions of different facial regions, thus the selection of discriminative features from prominent regions is crucial to the expression recognition. This paper proposes a novel method for facial expression recognition by exploring the most salient regions for each expression. The main contribution of this paper is using the complete feature set of expressions...
This paper presents a system to recognize face by a variation of LBPH. We use a method of regression of local binary features to get the landmark of face image whose computational complexity is very low. We utilize these landmark points which can be trained to align the face, to extract the facial features. By calculating the Local Binary Patterns Histogram (LBPH) of these landmark points and its...
Pose and illumination are considered as two main challenges that face recognition system encounters. In this paper, we consider face recognition problem across pose and illumination variations, given small amount of training samples and single sample per gallery (a.k.a., one shot classification). We combine the strength of 3D models in generating multiviews and various illumination samples and the...
Wide acceptance of biometrics as an authentication mode has led to investigation of multiple modalities such as face, periocular, iris for the long term robustness. Due to various deformities arising out of deteriorating health, need for enhancing the beauty by choice or to fix the injury as a result of trauma or aging, people tend to undergo surgery. However, such surgeries do not guarantee the restoration...
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...
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