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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...
In this paper, we propose a method for recognizing human actions indoors using fuzzy rules and multi cameras. To recognize the human actions, initially, we use the background difference method to extract human area candidates. We then extract HOG features and learn to detect humans using the features and AdaBoost. Fuzzy rules are then used of detect the human actions. The detected human is determined...
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...
A biometric-based techniques emerge as the promising approach for most of the real-time applications including security systems, video surveillances, human-computer interaction and many more. Among all biométrie methods, face recognition offers more benefits as compared to others. Diagnosing human faces and localizing them in images or videos is the priori step of tracking and recognizing. But the...
Local appearance descriptors are widely used on facial emotion recognition tasks. With these descriptors, image filters, such as Gabor wavelet or local binary patterns (LBP) are applied on the whole or specific regions of the face to extract facial appearance changes. But it is also clear that beside feature descriptor; choice of suitable learning method that integrates feature novelty is vital. The...
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...
Automatic 3D face registration is highly important for 3D face recognition, which can also be used in facial feature segmentation, facial mesh reconstruction, face synthesis and motion capture. In this paper, we propose a coarse-to-fine 3D face registration approach based on template matching of depth images and depth-based active appearance model (AAM). First we construct three multi-angle nose templates...
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...
In this paper, we propose a novel and robust approach for periocular recognition. Specifically, we propose fusion of Local Phase Quantization(LPQ) and Gabor wavelet descriptors to improve recognition performance and achieve robustness. We have utilized publicly available challenging still face images databases; MBGC v2.0, GTDB, PUT and Caltech. In the approach face is detected and normalized using...
A gender classification system uses human face from a given image to tell the gender of the given person. An effective gender classification approach is able to promote the improvement of many other applications, including image/video retrieval, security monitor, human-computer interaction, etc. In this paper, a method for gender classification task in frontal face images based on stacked-autoencoders...
The localization of eye centers technique is used in several applications. In this paper, we combine the face shape model to eye center location method to obtaining robustness in eye center localization from a low-resolution image. We make use of shape regression approach and combine it to the eye-center localization using isophote curvature features which has shown its advantage from previous work...
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...
Smile detection received a enormous attention due to its famous application as a ‘smile shutter’ in digital cameras. Edge Orientation Histograms (EOH) is one of the possible feature descriptors in a smile detector. This paper presents an evaluation of the use of Edge Orientation Histograms in a lip image based smile detector. The system built in this paper aims to discriminate lip images depicting...
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...
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