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.
Face recognition in extreme situations is still challenging to researchers. While several algorithms have shown great recognition results in ideal conditions, accuracy decreases when recognition tasks present a high illumination variation. In this paper, we propose to add two components to the recognition system to make the surf descriptor efficient in such extreme situations. First, we learn a discriminant...
With the development of artificial intelligence and pattern recognition, facial expression recognition plays a more and more important role in intelligent human-computer interaction. In this paper, we present a model named K-order emotional intensity model (K-EIM) which is based on K-Means clustering. Different from other related works, the proposed approach can quantify emotional intensity in an...
Being biological tissues in nature, all biometric traits undergo aging. Aging has profound effects on facial biometrics as it causes change in shape and texture. However aging remain an under-studied problem in comparison to facial variations due to pose, illumination and expression changes. A commonly adopted solution in the state-of-the-art is the virtual template synthesis for aging and de-aging...
Face recognition has been an area of interest among researchers in pattern recognition for the past few decades. Researches in face recognition are basically concentrated on texture based and geometry based features. The main advantage of Face recognition systems utilizing depth information is the availability of geometrical information of the face structure which is more or less unique for a subject...
In this paper, we propose an effective method for disguised face detection and recognition under the complex background. This method consists of two stages. The first stage determines whether the object is a person. In this stage, we propose the first-dynamic-then-static foreground object detection strategy. This strategy exploits the updated learning-based codebook model for moving object detection...
In this paper, a new type of hybrid method that hybridizes PCA and EBGM as a two-stage procedure is presented to improve recognition performance in large-scale face recognition. Among various methods in face recognition, PCA is considered to identify human faces by holistic views, while EBGM is supposed to distinguish one face from another by details, but they are both excellent representative methods...
Face recognition is crucial for human-robot interaction. Robot partners are required to work in real-time under unconstrained condition, yet, do not restrict the personal freedom of human occupants. On the other hand, due to its limited computational capability, a tradeoff between accuracy and computational load needs to be made. This tradeoff can be alleviated via the introduction of informationally...
An avatar is a representation of a real person in a virtual world and a user considers it as his/her secondary personal identity. With the spread of Virtual Reality(VR) technologies, there has been a user's growing interest in how to make an avatar to describe his/her identity well. Recent commercial games also support powerful avatar customization services to satisfy customer's various needs, but...
In this paper we present a comparative study of two well-known face recognition algorithms. The contribution of this work is to reveal the robustness of each FR algorithm with respect to various factors, such as variation in pose and low resolution of the images used for recognition. This evaluation is useful for practical applications where the types of the expected images are known. The two FR algorithms...
Human face based gender recognition is a challenging issue in image processing and machine vision domain. In this paper we proposed an approach for gender recognition using combination of statistical features and Local Binary Pattern (LBP). The optimal block size and statistical features set are determined by sequential forward floating selection (SFFS) algorithm for gender recognition improvement...
There are many social networking web sites used by people and number of photos is uploaded by them. But from photos it is difficult to predict the relationship among the people if necessary. So there is need of system for automatic identification and prediction of relationship among them, specifically kinship from photo. So, we proposed system, which uses Computer Vision, Face recognition, Feature...
We present a new technique to infer dimensions that can be used in biometric face recognition. The methodology is centered on inferring unique dimensions from human ears which provides unique physical biometric features. The process of determining the distance is done by harvesting the real actual dimensions from 2D faces images. This is achieved by using specific point to point distances on the two...
To overcome the shortcomings of the traditional methods, this paper proposes a novel face recognition method based on the image latent semantic features and ensemble extreme learning machine. The image latent semantic analysis is to acquire the high-level features from the face image, which has good robustness to illumination and expression changes. The image latent features are extracted as fellows:...
In this paper, we propose a new deep learning network “GENet”, it combines the multi-layer network architecture and graph embedding framework. Firstly, we use simplest unsupervised learning PCA/LDA as first layer to generate the low-level feature. Secondly, many cascaded dimensionality reduction layers based on graph embedding framework are applied to GENet. Finally, a linear SVM classifier is used...
Automatic detection of nose regions on 3D face images is highly important for 3D face registration and recognition. It can also be used in facial landmark detection which is important in facial feature segmentation, facial shape analysis, face synthesis and facial mesh reconstruction. In this paper, we propose a nose detection approach based on template matching of depth images. We have constructed...
Facial occlusion is a critical issue that may dramatically degrade the performance on facial expression-based emotion recognition. In this study, the Error Weighted Cross-Correlation Model (EWCCM) is employed to predict the facial Action Unit (AU) under partial facial occlusion from non-occluded facial regions for facial geometric feature reconstruction. In EWCCM, a Gaussian Mixture Model (GMM)-based...
Videos have ample amount of information in the form of frames that can be utilized for feature extraction and matching. However, face images in not all of the frames are “memorable” and useful. Therefore, utilizing all the frames available in a video for recognition does not necessarily improve the performance but significantly increases the computation time. In this research, we present a memorability...
Overweight and obesity is quite common in the modern society, which can result in many severe health problems. Thus weight loss has become a major event for many people to have a healthy living. A question is then raised for Biometrics or identity management: Is there any influence on face recognition when the facial shapes are varied, caused by body weight changes? No previous research has addressed...
Research focus in face recognition has shifted towards recognition of faces “in the wild” for both still images and videos which are captured in unconstrained imaging environments and without user cooperation. Due to confounding factors of pose, illumination, and expression, as well as occlusion and low resolution, current face recognition systems deployed in forensic and security applications operate...
In this paper, we propose a method for matching biometric data from disparate domains. Specifically, we focus on the problem of comparing a low-resolution (LR) image with a high-resolution (HR) one. Existing coupled mapping methods do not fully exploit the HR information or they do not simultaneously use samples from both domains during training. To this end, we propose a method that learns coupled...
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.