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We present Fermat, an Intelligent Social Network for Mathematics Learning, which integrates an Intelligent Tutoring System as an extra feature to help students to improve the teaching and learning process. The intelligent tutor takes into account both cognitive and affective aspects. The social network and the affective tutoring systems are accessed from the web. Initial results in math show the benefits...
In order to reduce the impact of image background and illumination in face locating, this dissertation has put forward a new algorithm to locate human eyes, applying YCbCr model to extract human face region, and then locating eyes correctly according to geometry and pixel features of human eyes. Experimental results show that this algorithm can be applicable in images with different backgrounds and...
Local spatiotemporal detectors and descriptors have recently become very popular for video analysis in many applications. They do not require any preprocessing steps and are invariant to spatial and temporal scales. Despite their computational simplicity, they have not been evaluated and tested for video analysis of facial data. This paper considers two space-time detectors and four descriptors and...
This paper propose an automatic method for facial features detection and then the image quality improvement methods to increase the rate of good recognition of a classifier based on appearance.
This paper focus on understanding human visual system when it decodes or recognizes facial expressions. Results presented can be exploited by the computer vision research community for the development of robust descriptor based on human visual system for facial expressions recognition. We have conducted psycho-visual experimental study to find which facial region is perceptually more attractive or...
Automatic emotion recognition from facial expression is one of the most intensively researched topics in affective computing and human-computer interaction. However, due to the lack of 3D feature and dynamic analysis the functional aspect of affective computing is insufficient for natural interaction. This paper presents an automatic emotion recognition approach from video sequences based on a fiducial...
We investigate body soft biometrics capabilities to perform pruning of a hard biometrics database improving both retrieval speed and accuracy. Our pre-classification step based on anthropometric measures is elaborated on a large scale medical dataset to guarantee statistical meaning of the results, and tested in conjunction with a face recognition algorithm. Our assumptions are verified by testing...
Face recognition, as one of the most interesting and successful applications of image understanding and machine vision, has grown a lot of attention during the past years. Basically human faces are very similar in structure with minor differences from person to person. In this paper a new robust face recognition method is proposed which exploit edge-based features of faces. The performance of this...
This paper presents advances on the Human ID Gait Challenge. Our method is based on combining an improved gait recognition method with an adapted low resolution face recognition method. For this, we experiment with a new automated segmentation technique based on alpha-matting. This allows better construction of feature images used for gait recognition. The same segmentation is also used as a basis...
Multiple research has shown the advantage of patch-based or local representation for face recognition. This paper builds on a novel way of putting the patches in context, using a foveated representation. While humans focus on local regions and move between them, they always see these regions in “context”. We hypothesize that using foveated context can improve performance of local region or patch based...
Face recognition is a biometric tool for authentication and verification having both research and practical relevance. A facial recognition based verification system can further be deemed a computer application for automatically identifying or verifying a person in a digital image. Varied and innovative face recognition systems have been developed thus far with widely accepted algorithms. The two...
Reference feedback contains the positive and negative feedback ranks. User¡¦s relevance feedback rank can derivate as the User¡¦s preference. In this paper, we addressed the user¡¦s relevance feedback technology to reflect the degree of user¡¦s preferences of what he liked. The personal preference and general preference could be considered in this paper. The dynamic re-ranking result will refer to...
Human aging face prediction is a popular research topic because of its various useful applications such as security system, missing persons search system, etc. In this study, we propose Exemplar-based Algorithm whose property considers the environment of human growth. Moreover, both the non-negative matrix factorization and linear interpolation methods are used to perform the prediction for six facial...
We present an Online Random Ferns (ORFs) classifier that progressively learns and builds enhanced models of object appearances. During the learning process, we allow the human intervention to assist the classifier and discard false positive training samples. The amount of human intervention is minimized and integrated within the online learning, such that in a few seconds, complex object appearances...
Automatic age classification from human faces is a challenging task which has recently attained an increasing attention. Most of the proposed approaches have however been mainly concerning controlled settings. In this paper, we propose a novel method for age classification in unconstrained conditions and provide extensive performance evaluation on benchmark datasets with standard protocols, thus allowing...
Face identification is the problem of determining whether two face images depict the same person or not. This is difficult due to variations in scale, pose, lighting, background, expression, hairstyle, and glasses. Thus, a powerful feature descriptor with local-deformation tolerance ability and discriminating capability is essential to fulfill all these variations. In this paper, we present a local...
Human faces undergo considerable amount of variations across ages. This paper proposes an age-invariant face verification method by using a Local Classifier Ensemble Model (LCEM). First, reference points are located based on an extended Active Shape Model and faces are aligned afterwards. Second, a face is grouped into several non-overlapping patches and each group is further divided into several...
Expression based face recognition has been gaining more and more attentions recently. Most traditional expression based face recognition can perform recognition where the probe and gallery have same expressions. In this paper, we propose to use different expressions for recognition. Our proposal exploits the temporal order in the video and extracts the identity signature from deformation and motion...
In this paper, an approach for human emotion recognition system based on Undecimated Wavelet Transform (UWT) is presented. The main drawback of Discrete Wavelet Transform (DWT) is not translation invariant. Translations of an image lead to different wavelet coefficients. UWT is used to overcome this and more comprehensive feature of the decomposed image is obtained. The classification of human emotional...
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