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This paper presents an implementation of face recognition, which is a very important task of identifying human faces. Representation of a face image is dealing with keypoints clustering and curve matching approach. In our work we implement the methods for recognition of a 3-D face image with missing and occluded part. The solutions for this problem is found out with the help of SIFT and RANSAC algorithms...
Automatic facial expression recognition has been drawn many attentions in both computer vision and artificial intelligence (AI) for the past decades. Although much progress has been made, facial expression recognition (FER) is still a challenging and interesting problem. In this paper, we propose a new FER system, which uses the active shape mode (ASM) algorithm to align the faces, then extracts local...
The deployment of cameras for security control allows for video stream to be used as input for face recognition (FR). However, most state of the art FR SDKs are generally specifically tuned for dealing with frontal and neutral face images, whereas expression and pose variations, which typically occur in unconstrained settings, e.g., video images, are still major challenges for reliable FR. In this...
This paper investigates the relationship between the extent of exaggeration in a caricature and its face identification ability. As face recognition is largely influenced by facial deformations, we focused on finding the borderline between likeness and unlikeness by applying gradual alterations to the face shape of the subject being studied. Suggestions on manipulating the degree of similarity when...
A dynamic facial expression recognition method based on the auto-regressive (AR) models using combined features of both shape and texture features is proposed in this paper. The AR model is effective to model complicated facial motions. In this work, six AR models are first learned for six basic expressions based on the fusion of shape and texture features of the difference between the neutral image...
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...
This paper proposes a novel machine-learning framework for facial-expression recognition, which is capable of processing images fast and accurately even without having to rely on a large-scale dataset. The framework is derived from Support Vector Machines (SVMs) but distinguishes itself in three key ways. First, the measure of the samples normalization is based on the Perturbed Subspace Method (PSM),...
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...
Large pose and illumination variations are very challenging for face recognition. The 3D Morphable Model (3DMM) approach is one of the effective methods for pose and illumination invariant face recognition. However, it is very difficult for the 3DMM to recover the illumination of the 2D input image because the ratio of the albedo and illumination contributions in a pixel intensity is ambiguous. Unlike...
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...
This paper presents a novel 3D facial expression recognition algorithm using Local Binary Patterns (LBP) under expression variations, which has been extensively adopted for facial analysis. First, to preserve the main information and remove noises which will affect the discrimination, BDPCA reconstruction and Shape Index is utilized to depict the human face accurately. Then the LBP framework for face...
Sketch recognition for forensic applications is a very challenging task and several solutions have been recently proposed. Considering that real mug shot databases can be very large, one important aspect to consider in this scenario is also the efficiency of the search procedure. This work proposes the use of shape features for a preliminary selection of the candidate photos to be successively analyzed...
In this study we propose a new set of muscle activity based features for facial expression recognition. We extract muscular activities by observing the displacements of facial feature points in an expression video. The facial feature points are initialized on muscular regions of influence in the first frame of the video. These points are tracked through optical flow in sequential frames. Displacements...
Roman coins play an important role to understand the Roman empire because they convey rich information about key historical events of the time. Moreover, as large amounts of coins are daily traded over the Internet, it becomes necessary to develop automatic coin recognition systems to prevent illegal trades. In this paper, we propose an automatic recognition method for ancient Roman coins. The proposed...
In this paper we address the problem of pose independent face recognition with a gallery set containing one frontal face image per enrolled subject while the probe set is composed by just a face image undergoing pose variations. The approach uses a set of aligned 3D models to learn deformation components using a 3D Morph able Model (3DMM). This further allows fitting a 3DMM efficiently on an image...
The work in this paper is dedicated to present and experiment a fully automatic face recognition approach based on exploiting the distinctive traits of 3D facial scans. We aim to present a recognition approach operates with fully and partial facial scans (missing facial parts). A region based approach for registration and recognition processes is adopted to offer robust faces matching against facial...
The Panorama of the face has a wider field of view, and it contains much more information of the head. After integration of human faces and ears, it can reduce computational complexity of the recognition process, and achieve a more robust non-intrusive multi-modal identification. This paper mainly focuses on building 3D face and ear panoramic image from 3D point cloud data. We extract the effective...
Extracting and understanding human emotion plays an important role in the interaction between humans and machine communication systems. The most expressive way to display human emotion is through facial expression analysis. In this paper, we propose a novel extraction and recognition method for facial expression and emotion on mobile cameras and formulate a classification model for facial emotions...
Recent years have witnessed a growing interest in developing methods for 3D face recognition. However, 3D scans often suffer from the problems of missing parts, large facial expressions, and occlusions. In this paper, we propose a novel general approach to deal with the 3D face recognition problem by making use of multiple keypoint descriptors (MKD) and the sparse representation-based classifier (SRC)...
With the rapid development of range image acquisition techniques, 3D computer vision has became a popular research area. It has numerous applications in various domains including robotics, biometrics, remote sensing, entertainment, civil construction, and medical treatment. Recently, a large number of algorithms have been proposed to address specific problems in the area of 3D computer vision. Meanwhile,...
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