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Book Two  and Three Dimensional Face Recognition Under Expression Variation

Download or read book Two and Three Dimensional Face Recognition Under Expression Variation written by Narges Hoda Mohammadzade and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Two  and Three Dimensional Patterns of the Face

Download or read book Two and Three Dimensional Patterns of the Face written by Peter W. Hallinan and published by CRC Press. This book was released on 1999-06-15 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: The human face is perhaps the most familiar and easily recognized object in the world, yet both its three-dimensional shape and its two-dimensional images are complex and hard to characterize. This book develops the vocabulary of ridges and parabolic curves, of illumination eigenfaces and elastic warpings for describing the perceptually salient fea

Book Towards Three dimensional Face Recognition in the Real

Download or read book Towards Three dimensional Face Recognition in the Real written by Huibin Li and published by . This book was released on 2013 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the natural, non-intrusive, easily collectible, widespread applicability, machine-based face recognition has received significant attention from the biometrics community over the past three decades. Compared with traditional appearance-based (2D) face recognition, shape-based (3D) face recognition is more stable to illumination variations, small head pose changes, and varying facial cosmetics. However, 3D face scans captured in unconstrained conditions may lead to various difficulties, such as non-rigid deformations caused by varying expressions, data missing due to self occlusions and external occlusions, as well as low-quality data as a result of some imperfections in the scanning technology. In order to deal with those difficulties and to be useful in real-world applications, in this thesis, we propose two 3D face recognition approaches: one is focusing on handling various expression changes, while the other one can recognize people in the presence of large facial expressions, occlusions and large pose various. In addition, we provide a provable and practical surface meshing algorithm for data-quality improvement. To deal with expression issue, we assume that different local facial region (e.g. nose, eyes) has different intra-expression/inter-expression shape variability, and thus has different importance. Based on this assumption, we design a learning strategy to find out the quantification importance of local facial regions in terms of their discriminating power. For facial description, we propose a novel shape descriptor by encoding the micro-structure of multi-channel facial normal information in multiple scales, namely, Multi-Scale and Multi-Component Local Normal Patterns (MSMC-LNP). It can comprehensively describe the local shape changes of 3D facial surfaces by a set of LNP histograms including both global and local cues. For face matching, Weighted Sparse Representation-based Classifier (W-SRC) is formulated based on the learned quantification importance and the LNP histograms. The proposed approach is evaluated on four databases: the FRGC v2.0, Bosphorus, BU-3DFE and 3D-TEC, including face scans in the presence of diverse expressions and action units, or several prototypical expressions with different intensities, or facial expression variations combine with strong facial similarities (i.e. identical twins). Extensive experimental results show that the proposed 3D face recognition approach with the use of discriminative facial descriptors can be able to deal with expression variations and perform quite accurately over all databases, and thereby has a good generalization ability. To deal with expression and data missing issues in an uniform framework, we propose a mesh-based registration free 3D face recognition approach based on a novel local facial shape descriptor and a multi-task sparse representation-based face matching process. [...].

Book Unconstrained Face Recognition

Download or read book Unconstrained Face Recognition written by Shaohua Kevin Zhou and published by Springer Science & Business Media. This book was released on 2005-11-30 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Face recognition has been actively studied over the past decade and continues to be a big research challenge. Just recently, researchers have begun to investigate face recognition under unconstrained conditions. Unconstrained Face Recognition provides a comprehensive review of this biometric, especially face recognition from video, assembling a collection of novel approaches that are able to recognize human faces under various unconstrained situations. The underlying basis of these approaches is that, unlike conventional face recognition algorithms, they exploit the inherent characteristics of the unconstrained situation and thus improve the recognition performance when compared with conventional algorithms. Unconstrained Face Recognition is structured to meet the needs of a professional audience of researchers and practitioners in industry. This volume is also suitable for advanced-level students in computer science.

Book New Approaches to Characterization and Recognition of Faces

Download or read book New Approaches to Characterization and Recognition of Faces written by Peter Corcoran and published by BoD – Books on Demand. This book was released on 2011-08-01 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: As a baby, one of our earliest stimuli is that of human faces. We rapidly learn to identify, characterize and eventually distinguish those who are near and dear to us. We accept face recognition later as an everyday ability. We realize the complexity of the underlying problem only when we attempt to duplicate this skill in a computer vision system. This book is arranged around a number of clustered themes covering different aspects of face recognition. The first section presents an architecture for face recognition based on Hidden Markov Models; it is followed by an article on coding methods. The next section is devoted to 3D methods of face recognition and is followed by a section covering various aspects and techniques in video. Next short section is devoted to the characterization and detection of features in faces. Finally, you can find an article on the human perception of faces and how different neurological or psychological disorders can affect this.

Book 3D Face Modeling  Analysis and Recognition

Download or read book 3D Face Modeling Analysis and Recognition written by Mohamed Daoudi and published by John Wiley & Sons. This book was released on 2013-06-11 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: 3D Face Modeling, Analysis and Recognition presents methodologies for analyzing shapes of facial surfaces, develops computational tools for analyzing 3D face data, and illustrates them using state-of-the-art applications. The methodologies chosen are based on efficient representations, metrics, comparisons, and classifications of features that are especially relevant in the context of 3D measurements of human faces. These frameworks have a long-term utility in face analysis, taking into account the anticipated improvements in data collection, data storage, processing speeds, and application scenarios expected as the discipline develops further. The book covers face acquisition through 3D scanners and 3D face pre-processing, before examining the three main approaches for 3D facial surface analysis and recognition: facial curves; facial surface features; and 3D morphable models. Whilst the focus of these chapters is fundamentals and methodologies, the algorithms provided are tested on facial biometric data, thereby continually showing how the methods can be applied. Key features: • Explores the underlying mathematics and will apply these mathematical techniques to 3D face analysis and recognition • Provides coverage of a wide range of applications including biometrics, forensic applications, facial expression analysis, and model fitting to 2D images • Contains numerous exercises and algorithms throughout the book

Book Face Recognition

    Book Details:
  • Author :
  • Publisher :
  • Release : 2005
  • ISBN :
  • Pages : 271 pages

Download or read book Face Recognition written by and published by . This book was released on 2005 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Face Recognition Using Three Dimensional and Multimodal Images

Download or read book Face Recognition Using Three Dimensional and Multimodal Images written by Claudio Cusano and published by LAP Lambert Academic Publishing. This book was released on 2011-10 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: The great attention received by face recognition is motivated not only by the fundamental challenges posed by the problem, but also by numerous practical applications. Although current automatic recognition systems have reached a certain level of reliability, their success is limited by the conditions imposed by many practical applications. The recent improvements in three-dimensional acquisition devices allows the implementation of three-dimensional face recognition systems. Some devices incorporate a color digital camera that allows the acquisition of multimodal 2D+3D images, which can be exploited to design more reliable systems. This work investigates face recognition strategies based on the analysis of three-dimensional and multimodal images. The topics addressed include 3D face face detection and normalization, geometric features, information fusion strategies and recognition of partially occluded faces.

Book Facial Multi characteristics And Applications

Download or read book Facial Multi characteristics And Applications written by Bob Zhang and published by World Scientific. This book was released on 2018-11-19 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: What features or information can we observe from a face, and how can these information help us to understand the person concerned, in terms of their well-being and what can we learn about and from each given feature? This book answers these questions by first dividing a face's multiple characteristics into two main categories: original (or physiological) features and features that change over a lifetime. The first category, original features, may be further divided into two sub-classes: features special (or unique) to an individual, and features common to a particular group. The second, changed features, can also be subdivided into two groups: features altered due to disease or features altered by other external factors. From these four sub-categories, four different applications — facial identification using original and special features; beauty analysis using original common features; facial diagnosis by disease changed features; and expression recognition through affect-changed features — are identified.The book will benefit researchers, professionals, and graduate students working in the field of computer vision, pattern recognition, security/clinical practice, and beauty analysis, and will also be useful for interdisciplinary research.

Book Efficient 3D face recognition based on PCA

Download or read book Efficient 3D face recognition based on PCA written by Yagnesh Parmar and published by GRIN Verlag. This book was released on 2012-11-05 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt: Project Report from the year 2012 in the subject Engineering - Computer Engineering, Gujarat University, course: Electronics and communication, language: English, abstract: This thesis describes a face recognition system that overcomes the problem of changes in gesture and mimics in three-dimensional (3D) range images. Here, we propose a local variation detection and restoration method based on the two-dimensional (2D) principal component analysis (PCA). The depth map of a 3D facial image is first smoothed using median filter to minimize the local variation. The detected face shape is cropped & normalized to a standard image size of 101x101 pixels and the forefront nose point is selected to be the image center. Facial depthvalues are scaled between 0 and 255 for translation and scaling-invariant identification. The preprocessed face image is smoothed to minimize the local variations. The 2DPCA is applied to the resultant range data and the corresponding principal-(or eigen-) images are used as the characteristic feature vectors of the subject to find his/her identity in the database of pre-recorded faces. The system's performance is tested against the GavabDB facial databases. Experimental results show that the proposed method is able to identify subjects with different gesture and mimics in the presence of noise in their 3D facial image.

Book Three dimensional Face Recognition

Download or read book Three dimensional Face Recognition written by Georgios Passalis and published by . This book was released on 2004 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Three Dimensional Face Recognition Using Two Dimensional Principal Component Analysis

Download or read book Three Dimensional Face Recognition Using Two Dimensional Principal Component Analysis written by Inad A. Aljarrah and published by . This book was released on 2006 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: The system's performance is tested against the GavabDB and Notre Dame University facial databases. Experimental results show that the proposed method is able to identify subjects with different gesture and mimics in the presence of noise in their 3D facial images.

Book Recent Advances in Face Recognition

Download or read book Recent Advances in Face Recognition written by Kresimir Delac and published by BoD – Books on Demand. This book was released on 2008-12-01 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main idea and the driver of further research in the area of face recognition are security applications and human-computer interaction. Face recognition represents an intuitive and non-intrusive method of recognizing people and this is why it became one of three identification methods used in e-passports and a biometric of choice for many other security applications. This goal of this book is to provide the reader with the most up to date research performed in automatic face recognition. The chapters presented use innovative approaches to deal with a wide variety of unsolved issues.

Book Face Detection and Modeling for Recognition

Download or read book Face Detection and Modeling for Recognition written by Rein-Lien Hsu and published by . This book was released on 2002 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Face recognition has received substantial attention from researchers in biometrics, computer vision, pattern recognition, and cognitive psychology communities because of the increased attention being devoted to security, man-machine communication, content-based image retrieval, and image/video coding. We have proposed two automated recognition paradigms to advance face recognition technology. Three major tasks involved in face recognition systems are: (i) face detection, (ii) face modeling, and (iii) face matching. We have developed a face detection algorithm for color images in the presence of various lighting conditions as well as complex backgrounds. Our detection method first corrects the color bias by a lighting compensation technique that automatically estimates the parameters of reference white for color correction. We overcame the difficulty of detecting the low-luma and high-luma skin tones by applying a nonlinear transformation to the Y CbCr color space. Our method generates face candidates based on the spatial arrangement of detected skin patches. We constructed eye, mouth, and face boundary maps to verify each face candidate. Experimental results demonstrate successful detection of faces with different sizes, color, position, scale, orientation, 3D pose, and expression in several photo collections. 3D human face models augment the appearance-based face recognition approaches to assist face recognition under the illumination and head pose variations. For the two proposed recognition paradigms, we have designed two methods for modeling human faces based on (i) a generic 3D face model and an individual's facial measurements of shape and texture captured in the frontal view, and (ii) alignment of a semantic face graph, derived from a generic 3D face model, onto a frontal face image.

Book 3d Facial Feature Extraction and Recognition

Download or read book 3d Facial Feature Extraction and Recognition written by Sokyna Al-Qatawneh and published by LAP Lambert Academic Publishing. This book was released on 2012-05 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently with the development of more affordable 3D acquisition systems and the availability of 3D face databases, 3D face recognition has been attracting interest to tackle the limitations in performance of most existing 2D systems. In this research, we introduce a robust automated 3D Face recognition system that implements 3D data of faces with different facial expressions, hair, shoulders, clothing, etc., extracts features for discrimination and uses machine learning techniques to make the final decision. A novel system for automatic processing for 3D facial data has been implemented using multi stage architecture; in a pre-processing and registration stage the data was standardized, spikes were removed, holes were filled and the face area was extracted. Then the nose region, which is relatively more rigid than other facial regions in an anatomical sense, was automatically located and analysed by computing the precise location of the symmetry plane. Then useful facial features and a set of effective 3D curves were extracted. Finally, the recognition and matching stage was implemented by using CCNN and SVM for classification, and the KNN algorithms for matching.

Book 3D Face Recognition System Based on 3D Eigenfaces

Download or read book 3D Face Recognition System Based on 3D Eigenfaces written by Divyarajsinh Parmar and published by LAP Lambert Academic Publishing. This book was released on 2013 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt: A face recognition system that solves the problem of changes in facial expression and mimics in 3D range images. So here, we propose a local variation detection and restoration method based eigenfaces using the principal component analysis (PCA). The depth map of a 3D facial image is first smoothed using median filter to minimize the local variation. The forefront nose point is selected to be the image center for alignment. The detected face shape is cropped & normalized to a standard image size of 101x101 pixels. Facial depth-valus are scaled between 0 and 255 for translation and scaling-invariant identification. The preprocessed face image is smoothed to minimize the local variations. The PCA is applied to the resultant range data and the corresponding principal or Eigen images are used as the characteristic feature vectors of the subject to find the person identity in the database of pre-recorded faces. The system performance is tested on the GavabDB databases. Experimental results show that the proposed method is able to identify subjects with different facial expression and mimics in the presence of noise in their 3D facial images.

Book Representations of 3D Faces

Download or read book Representations of 3D Faces written by Mayur Mudigonda and published by . This book was released on 2010 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: