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Nowadays, with the increasing use of biometric data, it is expected that systems can give successful results against difficult situations and work robustly. Especially, in face recognition systems, variables such as direction of light, facial expression and reflection are making difficult to identify. Thus, in recent years, Convolutional Neural Network (CNN) models, which are deep learning models...
Even though there has been enormous research in facial analysis and more sophisticated algorithm, face recognition fails drastically in real time when the facial images are occluded. This paper explains the algorithm and technical concepts behind the high accurate face recognition systems for a 2D frontal images with occlusion for a business requirments. Face recognition is implemented using Convolutional...
One of the most logical applications of face recognition for authentication is on mobile handset devices. However, face recognition still faces challenges in providing environment tolerance: being able to compensate for changes in light conditions within an environment where authentication is occurring, due to users carrying their mobile handset devices to different locations with varying and unpredictable...
Deep learning is the research focus in the recent years. Because of its excellent performance.it is widely used in the area of pattern recognition. Facial feature is useful for a variety of tasks, the application of deep learning in this area is also developing fast. We introduce some recent research work in this domain, and show the potential of it.
Dictionary learning has been applied to computer vision problems such as facial expression recognition. K-SVD is one of the state-of-the-art dictionary learning algorithms. However, K-SVD is unsupervised and focuses only on the representational power. In this paper, we adopt label-consistent K-SVD with scattering transform in facial expression recognition. In addition to reducing the reconstruction...
This paper proposes a video retargeting method. The method makes multimedia more suitable for ubiquitous video access, including comfortable watching, interesting region detection and safety transmitting. Because of the rapid progress of electronic commercial product, video service needs to adapt different device. There are some challenges: First at all, the resolution, aspect ratio and size of display...
Face recognition and verification is still a challenging problem due to several issues such as pose, facial expression, occlusion, imaging conditions, rotation, size and orientation. This paper addresses the problem of recognizing human faces despite the presence in pose and size variation. To handle these problems, we mainly focus on block size definition. Instead of uniform block we thus propose...
In this paper, it is shown that Local Zernike Moments which is used in object and face recognition applications succesfully, can also used for face-pair matching problem. In this study, instead of using feature vectors produced by LZM directly, we focussed on reducing the dimensions of feature vectors and increasing the performance. In the light of experimental results, a new method called L2ML-YZM...
In this study we propose a set of anatomy based features for facial expression recognition. The muscle forces that constitute an expression are solved by tracking carefully selected facial feature points. These points are initialized in the muscular regions of influence on the first frame of the video. They are tracked using the optical flow algorithm. The displacements of facial feature points are...
Many modern computer vision systems combine high dimensional features and linear classifiers to achieve better classification accuracy. However, the excessively long features are often highly redundant; thus dramatically increases the system storage and computational load. This paper presents a novel feature selection algorithm, namely cardinal sparse partial least square algorithm, to address this...
This work introduces a real-time video-based open-set face recognition system. The system has been developed for the identification of people who stand in front of an interactive screen to communicate with a virtual application. The system uses Discrete Cosine Transform (DCT) features obtained from non-overlapping 20 blocks, and Support Vector Machines (SVM) based verifiers are employed for the classification...
Automatic recognition of facial expression remains a challenging task in computer vision, because of large amount of image data and subtle difference in facial expressions. In this paper, we present a customizable system for facial expression recognition using non-negative matrix factorization (NMF). Our system can be described in two major phases: the first phase uses preprocessing and the NMF for...
Face recognition is a very challenging problem in computer vision. In this paper, Speeded up Robust Features (SURF), a scale and rotation invariant interesting point descriptor, is further explored for face recognition. Specially, a novel technique, Cell Similarity is proposed to make improvement based on SURF in face recognition. In the meantime, different cell division strategies are proposed and...
In this paper, we address the problem of estimating the 3D structure and motion of a non-rigid object based on feature points throughout a image sequence. The main limitation of existing factorization methods is that they are difficult to provide correct structure and motion estimates: the motion matrix has a repetitive structure which is not represented by these methods. In order to cope with this...
This paper presents a new framework for facial expression recognition based on diffeomorphic matching. First landmarks are selected based on a manual or automatic method. All of the landmarks from different images are registered to a reference landmark set using a rigid registration algorithm. The pair-wise geodesic distance between all sets of landmarks are then computed using diffeomorphic matching...
In this work, we developed a technique for face recognition using the idea of multiresolution face recognition. The multiresolution subbands are generated by using discrete wavelet transform (DWT). We then apply scale invariant feature transform (SIFT) to extract the salient feature descriptors at each subband using the resulting low frequency subband of the image. The descriptors are used to perform...
Identity-invariant estimation of head pose from still images is a challenging task due to the high variability of facial appearance. We present a novel 3D head pose estimation approach, which utilizes the flexibility and expressibility of a dense generative 3D facial model in combination with a very fast fitting algorithm. The efficiency of the head pose estimation is obtained by a 2D synthesis of...
We develop a model for face recognition that describes the image as a sum of signal and noise components. We describe each component as a weighted combination of basis functions. In this paper we investigate the effect of the degree of localization of these basis functions: each might describe the whole image (describe global pixel covariance) or only a small part of the face (describe only local...
Subspaces offer convenient means of representing information in many Pattern Recognition, Machine Vision, and Statistical Learning applications. Contrary to the growing popularity of subspace representations, the problem of efficiently searching through large subspace databases has received little attention in the past. In this paper we present a general solution to the Approximate Nearest Subspace...
Robust face image modeling under uncontrolled conditions is crucial for the current face recognition systems in practice. One approach is to seek a compact representation of the given image set which encodes the intrinsic lower dimensional manifold of them. Among others, Local Linear Embedding (LLE) is one of the most popular method for that purpose. However, it suffers from the following problems...
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