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. [...].
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.
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:
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
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
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.
Download or read book Three dimensional Face Recognition written by Michael M. Bronstein and published by . This book was released on 2005 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Guide to Biometric Reference Systems and Performance Evaluation written by Dijana Petrovska-Delacrétaz and published by Springer Science & Business Media. This book was released on 2009-04-05 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biometrics has moved from using fingerprints to using many methods of assessing human physical and behavioral traits. This guide introduces a new performance evaluation framework designed to offer full coverage of performance evaluation of biometric systems.
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:
Download or read book 3d Face Registration written by Nese Alyüz and published by LAP Lambert Academic Publishing. This book was released on 2009-11 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: Three dimensional (3D) face recognition is a frequently used biometric and its performance is dependent on registration. Registration aligns two faces and makes a comparison possible between the two surfaces. In the literature, best results have been achieved by a one-to-all approach, where a test face is aligned to each gallery face separately. To overcome the computational bottleneck of this approach, we examine registration based on an Average Face Model (AFM). To improve the registration, we propose to group faces and register with category-specific AFMs. We see that gender and morphology classes exist, when faces are categorized with the clustering approach. As another factor causing diversity in the face space, we explore expression variations. To reduce the negative effect of expressions in registration, we divide the facial surface into logical segments, and for each segment we create an Average Region Model (ARM). Registering via each ARM separately, we examine regional recognition performance. Even though some regions are less affected by expression variations, no single region is sufficient by itself and the use of all regions is beneficial.
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.
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:
Download or read book Robust Face Recognition Based on Three Dimensional Data written by Di Huang and published by . This book was released on 2011 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: The face is one of the best biometrics for person identification and verification related applications, because it is natural, non-intrusive, and socially weIl accepted. Unfortunately, an human faces are similar to each other and hence offer low distinctiveness as compared with other biometrics, e.g., fingerprints and irises. Furthermore, when employing facial texture images, intra-class variations due to factors as diverse as illumination and pose changes are usually greater than inter-class ones, making 2D face recognition far from reliable in the real condition. Recently, 3D face data have been extensively investigated by the research community to deal with the unsolved issues in 2D face recognition, Le., illumination and pose changes. This Ph.D thesis is dedicated to robust face recognition based on three dimensional data, including only 3D shape based face recognition, textured 3D face recognition as well as asymmetric 3D-2D face recognition. In only 3D shape-based face recognition, since 3D face data, such as facial pointclouds and facial scans, are theoretically insensitive to lighting variations and generally allow easy pose correction using an ICP-based registration step, the key problem mainly lies in how to represent 3D facial surfaces accurately and achieve matching that is robust to facial expression changes. In this thesis, we design an effective and efficient approach in only 3D shape based face recognition. For facial description, we propose a novel geometric representation based on extended Local Binary Pattern (eLBP) depth maps, and it can comprehensively describe local geometry changes of 3D facial surfaces; while a 81FT -based local matching process further improved by facial component and configuration constraints is proposed to associate keypoints between corresponding facial representations of different facial scans belonging to the same subject. Evaluated on the FRGC v2.0 and Gavab databases, the proposed approach proves its effectiveness. Furthermore, due tq the use of local matching, it does not require registration for nearly frontal facial scans and only needs a coarse alignment for the ones with severe pose variations, in contrast to most of the related tasks that are based on a time-consuming fine registration step. Considering that most of the current 3D imaging systems deliver 3D face models along with their aligned texture counterpart, a major trend in the literature is to adopt both the 3D shape and 2D texture based modalities, arguing that the joint use of both clues can generally provides more accurate and robust performance than utilizing only either of the single modality. Two important factors in this issue are facial representation on both types of data as well as result fusion. In this thesis, we propose a biological vision-based facial representation, named Oriented Gradient Maps (OGMs), which can be applied to both facial range and texture images. The OGMs simulate the response of complex neurons to gradient information within a given neighborhood and have properties of being highly distinctive and robust to affine illumination and geometric transformations. The previously proposed matching process is then adopted to calculate similarity measurements between probe and gallery faces. Because the biological vision-based facial representation produces an OGM for each quantized orientation of facial range and texture images, we finally use a score level fusion strategy that optimizes weights by a genetic algorithm in a learning pro cess. The experimental results achieved on the FRGC v2.0 and 3DTEC datasets display the effectiveness of the proposed biological vision-based facial description and the optimized weighted sum fusion. [...].
Download or read book Biometrics and Identity Management written by Ben Schouten and published by Springer. This book was released on 2008-12-23 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: A key driving factor for biometrics is the widespread national and international depl- ment of biometric systems that has been initiated in the past two years and is about to accelerate. While nearly all current biometric deployments are government-led and pr- cipally concerned with national security and border control scenarios, it is now apparent that the widespread availability of biometrics in everyday life will also spin out an ev- increasing number of (private) applications in other domains. Crucial to this vision is the management of the user’s identity, which does not only imply the creation and update of a biometric template, but requires the development of instruments to properly handle all the data and operations related to the user identity. COST Action 2101 on Biometrics for Identity Documents and Smart Cards has - erated as a valuable and effective platform for close collaboration of European sci- tists from academia and industry researching biometrics for identity documents and smartcards. This has led to the continuous advances achieved in various classes of biometrics and their implementations in the identity management domain. These c- tributions to knowledge in this field were first presented at the First European Wo- shop on Biometrics and Identity Management (BioID 2008) organized in Roskilde, Denmark during May 7–9, 2008.
Download or read book Advances in Visual Computing written by George Bebis and published by Springer Nature. This book was released on 2019-10-25 with total page 718 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th International Symposium on Visual Computing, ISVC 2019, held in Lake Tahoe, NV, USA in October 2019. The 100 papers presented in this double volume were carefully reviewed and selected from 163 submissions. The papers are organized into the following topical sections: Deep Learning I; Computer Graphics I; Segmentation/Recognition; Video Analysis and Event Recognition; Visualization; ST: Computational Vision, AI and Mathematical methods for Biomedical and Biological Image Analysis; Biometrics; Virtual Reality I; Applications I; ST: Vision for Remote Sensing and Infrastructure Inspection; Computer Graphics II; Applications II; Deep Learning II; Virtual Reality II; Object Recognition/Detection/Categorization; and Poster.
Download or read book Data Driven 3D Facial Animation written by Zhigang Deng and published by Springer Science & Business Media. This book was released on 2008 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-Driven 3D Facial Animation systematically describes the important techniques developed over the last ten years or so. Comprehensive in scope, the book provides an up-to-date reference source for those working in the facial animation field.
Download or read book Handbook of Pattern Recognition and Computer Vision written by C. H. Chen and published by World Scientific. This book was released on 1999 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference.
