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31
Recognizing rotated faces from frontal and side views: An approach toward effective use of mugshot databases
, 2008
"... Mug shot photography has been used to identify criminals by the police for more than a century. However, the common scenario of face recognition using frontal and side-view mug shots as gallery remains largely uninvestigated in comput-erized face recognition across pose. This paper presents a novel ..."
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Cited by 15 (2 self)
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Mug shot photography has been used to identify criminals by the police for more than a century. However, the common scenario of face recognition using frontal and side-view mug shots as gallery remains largely uninvestigated in comput-erized face recognition across pose. This paper presents a novel appearance-based approach using frontal and sideface images to handle pose variations in face recognition, which has great potential in forensic and security applications involving police mugshot databases. Virtual views in different poses are generated in two steps: 1) shape modelling and 2) texture synthesis. In the shape modelling step, a multilevel variation minimization approach is applied to generate personalized 3-D face shapes. In the texture synthesis step, face surface properties are analyzed and virtual views in arbitrary viewing conditions are rendered, taking diffuse and specular reflections into account. Appearance-based face recognition is performed with the augmentation of synthesized virtual views covering possible viewing angles to recognize probe views in arbitrary conditions. The encouraging experimental results demonstrated that the proposed approach by using frontal and side-view images is a feasible and effective solution to recognizing rotated faces, which can lead to a better and practical use of existing forensic databases in computerized human face-recognition applications.
Face shape recovery from a single image using cca mapping between tensor spaces
- In Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition
, 2008
"... In this paper, we propose a new approach for face shape recovery from a single image. A single near infrared (NIR) image is used as the input, and a mapping from the NIR tensor space to 3D tensor space, learned by using statistical learning, is used for the shape recovery. In the learning phase, the ..."
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Cited by 9 (2 self)
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In this paper, we propose a new approach for face shape recovery from a single image. A single near infrared (NIR) image is used as the input, and a mapping from the NIR tensor space to 3D tensor space, learned by using statistical learning, is used for the shape recovery. In the learning phase, the two tensor models are constructed for NIR and 3D images respectively, and a canonical correlation analysis (CCA) based multi-variate mapping from NIR to 3D faces is learned from a given training set of NIR-3D face pairs. In the reconstruction phase, given an NIR face image, the depth map is computed directly using the learned mapping with the help of tensor models. Experimental results are provided to evaluate the accuracy and speed of the method. The work provides a practical solution for reliable and fast shape recovery and modeling of 3D objects. 1.
Video-based Face Recognition: A Survey
"... Abstract—During the past several years, face recognition in video has received significant attention. Not only the wide range of commercial and law enforcement applications, but also the availability of feasible technologies after several decades of research contributes to the trend. Although curren ..."
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Cited by 7 (0 self)
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Abstract—During the past several years, face recognition in video has received significant attention. Not only the wide range of commercial and law enforcement applications, but also the availability of feasible technologies after several decades of research contributes to the trend. Although current face recognition systems have reached a certain level of maturity, their development is still limited by the conditions brought about by many real applications. For example, recognition images of video sequence acquired in an open environment with changes in illumination and/or pose and/or facial occlusion and/or low resolution of acquired image remains a largely unsolved problem. In other words, current algorithms are yet to be developed. This paper provides an up-to-date survey of video-based face recognition research. To present a comprehensive survey, we categorize existing video based recognition approaches and present detailed descriptions of representative methods within each category. In addition, relevant topics such as real time detection, real time tracking for video, issues such as illumination, pose, 3D and low resolution are covered. Keywords—Face recognition, video-based, survey I.
Fully automatic expression-invariant face correspondence
- Machine Vision and Applications
, 2014
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Reconstruction of 3D Human Facial Images Using Partial Differential Equations
"... Abstract—One of the challenging problems in geometric modeling and computer graphics is the construction of realistic human facial geometry. Such geometry are essential for a wide range of applications, such as 3D face recognition, virtual reality applications, facial expression simulation and compu ..."
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Cited by 4 (0 self)
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Abstract—One of the challenging problems in geometric modeling and computer graphics is the construction of realistic human facial geometry. Such geometry are essential for a wide range of applications, such as 3D face recognition, virtual reality applications, facial expression simulation and computer based plastic surgery application. This paper addresses a method for the construction of 3D geometry of human faces based on the use of Elliptic Partial Differential Equations (PDE). Here the geometry corresponding to a human face is treated as a set of surface patches, whereby each surface patch is represented using four boundary curves in the 3-space that formulate the appropriate boundary conditions for the chosen PDE. These boundary curves are extracted automatically using 3D data of human faces obtained using a 3D scanner. The solution of the PDE generates a continuous single surface patch describing the geometry of the original scanned data. In this study, through a number of experimental verifications we have shown the efficiency of the PDE based method for 3D facial surface reconstruction using scan data. In addition to this, we also show that our approach provides an efficient way of facial representation using a small set of parameters that could be utilized for efficient facial data storage and verification purposes. Index Terms—Partial Differential Equations, 3D face representation, 3D data storage.
PCA-based 3D face photography
- In Brazilian Symposium on Computer Graphics and Image Processing
, 2008
"... This paper presents a 3D face photography system based on a small set of training facial range images. The training set is composed by 2D texture and 3D range images (i.e. geometry) of a single subject with different facial expressions. The basic idea behind the method is to create texture and geome ..."
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Cited by 4 (4 self)
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This paper presents a 3D face photography system based on a small set of training facial range images. The training set is composed by 2D texture and 3D range images (i.e. geometry) of a single subject with different facial expressions. The basic idea behind the method is to create texture and geometry spaces based on the training set and transformations to go from one space to the other. The main goal of proposed approach is to obtain a geometry representation of a given face provided as a texture image, which undergoes a series of transformations through the texture and geometry spaces. Facial feature points are obtained by an active shape model (ASM) extracted from the 2D gray-level images. PCA then is used to represent the face dataset, thus defining an orthonormal basis of texture and range data. An input face is given by a gray-level face image to which the ASM is matched. The extracted ASM is fed to the PCA basis representation and a 3D version of the 2D input image is built. The experimental results on static images and video sequences using seven samples as training dataset show rapid reconstructed 3D faces which maintain spatial coherence similar to the human perception, thus corroborating the efficiency of our approach. 1.
3D face texture modeling from uncalibrated frontal and profile images
- Proc. IEEE BTAS
, 2012
"... 3D face modeling from 2D face images is of significant importance for face analysis, animation and recognition. Previous research on this topic mainly focused on 3D face modeling from a single 2D face image; however, a single face image can only provide a limited description of a 3D face. In many ap ..."
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Cited by 1 (1 self)
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3D face modeling from 2D face images is of significant importance for face analysis, animation and recognition. Previous research on this topic mainly focused on 3D face modeling from a single 2D face image; however, a single face image can only provide a limited description of a 3D face. In many applications, for example, law enforcement, multi-view face images are usually captured for a subject during enrollment, which makes it desirable to build a 3D face texture model, given a pair of frontal and profile face images. We first determine the correspondence between uncalibrated frontal and profile face images through facial landmark alignment. An initial 3D face shape is then reconstructed from the frontal face image, followed by shape refinement utilizing the depth information provided by the profile image. Finally, face texture is extracted by mapping the frontal face image on the recovered 3D face shape. The proposed method is utilized for 2D face recognition in two scenarios: (i) normalization of probe image, and (ii) enhancing the representation capability of gallery set. Experimental results comparing the proposed method with a state-of-the-art commercial face matcher and densely sampled LBP on a subset of the FERET database show the effectiveness of the proposed 3D face texture model. 1.
Face Shape Reconstruction from Image Sequence Taken with Monocular Camera using Shape Database
- Proc. 14th International Conference on Image Analysis and Processing (ICIAP 2007
"... We propose a method for reconstructing 3D face shape from a camera, which captures the object face from various viewing angles. In this method, we do not directly reconstruct the shape, but estimate a small number of parameters which represent the face shape. The parameter space is constructed with ..."
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Cited by 1 (1 self)
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We propose a method for reconstructing 3D face shape from a camera, which captures the object face from various viewing angles. In this method, we do not directly reconstruct the shape, but estimate a small number of parameters which represent the face shape. The parameter space is constructed with Principal Component Analysis of database of a large number of face shapes collected for different people. By the PCA, the parameter space can represent the shape difference for the faces of various persons. From the input image sequence that is captured by the moving camera, the parameters of the object face can be estimated based on optimization framework. The experiments based on the proposed method demonstrate that the proposed method can reconstruct the facial shape with the accuracy of 2.5mm averaged error. 1.
Inter-image outliers and their application to image classification
, 2010
"... Image variability that is impossible or difficult to restore by intra-image processing, such as the variability caused by occlusions, significantly reduces the performance of image-recognition methods. To address this issue, we propose that the pixels associated with large distances obtained by inte ..."
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Cited by 1 (1 self)
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Image variability that is impossible or difficult to restore by intra-image processing, such as the variability caused by occlusions, significantly reduces the performance of image-recognition methods. To address this issue, we propose that the pixels associated with large distances obtained by inter-image pixel-by-pixels comparisons should be considered as inter-image outliers and should be removed from the similarity calculation used for the image classification. When this method is combined with the template-matching method for image recognition, it leads to state-of-the-art recognition performance: 91 % with AR database that includes occluded face images, 90 % with PUT database that includes pose variations of face images and 100 % with EYale B database that includes images with large illumination variation.
Heterogeneous Specular and Diffuse 3-D Surface Approximation for Face Recognition Across Pose
"... Abstract—This paper proposes a novel heterogeneous specular and diffuse (HSD) 3-D surface approximation which considers spatial variability of specular and diffuse reflections in face modelling and recognition. Traditional 3-D face modelling and recognition methods constrain human faces with either ..."
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Abstract—This paper proposes a novel heterogeneous specular and diffuse (HSD) 3-D surface approximation which considers spatial variability of specular and diffuse reflections in face modelling and recognition. Traditional 3-D face modelling and recognition methods constrain human faces with either the Lam-bertian assumption or the homogeneity assumption, resulting in suboptimal shape and texture models. The proposed HSD approach allows both specular and diffuse reflectance coefficients to vary spatially to better accommodate surface properties of real human faces. From a small number of face images of a person under different lighting conditions, 3-D shape and surface reflectivity property are estimated using a localized stochastic optimization method. The resultant personalized 3-D face model is used to render novel gallery views under different poses for recognition across pose. The proposed approach is evaluated on both synthetic and real face datasets and benchmarked against the state-of-the-art approaches. Experimental results demonstrated that it can achieve a higher level of performances in modelling accuracy, algorithm reliability, and recognition accuracy, which suggests that face modelling and recognition beyond the Lamber-tian and homogeneity assumptions is a feasible and better solution towards pose-invariant face recognition. Index Terms—3-D modelling, face approximation, face recogni-tion, heterogeneity, pose variation, reflectivity. I.
