Download or read book Robust Signatures for 3D Face Registration Recognition written by Prathap M. Nair and published by . This book was released on 2009 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Robust Signatures for 3D Face Registration and Recognition written by Prathap N. Nair and published by . This book was released on 2009 with total page 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 Machine Learning Based 3D Face Biometrics with Local Low level Geometrical Features written by Yinjie Lei and published by . This book was released on 2013 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: [Truncated abstract] Biometrics has been an active research area due to its enormous potential applications in video surveillance, human-machine interaction and access control systems. Among the biometric traits, the human face is the most publicly accepted biometric because of its non-intrusiveness and easy data acquisition. Most of the work on face recognition has been accomplished using 2D data. 2D face recognition systems are not robust to variations in pose, illumination conditions and facial expressions. With the rapid advancements in the development of data capturing technologies (e.g. Minolta Vivid and Microsoft Kinect), the acquisition of 3D data is becoming a more feasible task. 3D data processing has the potential to overcome the limitations and drawbacks faced by 2D facial data. Most of the existing 3D face recognition systems rely on the surface registration of the gallery and probe faces and/or on complex feature matching techniques. These methods are sensitive to facial expression and computationally expensive and are not suitable for real-world applications. In this thesis, we present novel algorithms based on low-level geometrical signatures which can be extracted at a low computational cost. To address the issue of facial expression variations, we adopt various machine learning techniques. This thesis is organized as a set of papers published in journals or currently under review. Three different local geometric feature based approaches have been proposed and their efficiency has been demonstrated through extensive experimental evaluations on the largest publicly available 3D face datasets. First, a fast and fully automatic approach based on four kinds of low-level geometrical features collected from the semi-rigid facial regions was devised and used to represent 3D faces. As a result, the effects of the deformed facial regions are avoided. The extracted features revealed to be efficient in computation and robust in the presence of facial expressions. A region-based histogram descriptor computed from these features was used as a single feature vector for a 3D face. The resulting feature vectors are independent of the coordinate system and hence can be tolerant to minor pose variations. A Support Vector Machine (SVM) was then trained as a classifier based on the proposed histogram descriptors to recognize any test face. In order to combine the contributions of the two semi-rigid facial regions (eyesforehead and nose), both feature-level and score-level fusion schemes are tested and compared. The experimental results demonstrate that feature-level fusion achieves a higher performance compared to score-level fusion. Second, in order to further increase the computational efficiency and robustness, a computationally efficient 3D face recognition approach is presented based on a novel facial signature called Angular Radial Signature (ARS). This approach extracts a set of ARS features from the semi-rigid regions of a 3D face. It was demonstrated that the extraction of these signatures is highly efficient (low computational cost). The Kernel Principal Component Analysis (KPCA) is subsequently used to extract the mid-level features from the ARSs to achieve a greater discriminative power and to deal with the linearly inseparable classification problem...

Download or read book Analysis of 3D Face Recognition Robust to Expressions and Occlusions written by A. S. Gavali and published by . This book was released on 2016-04-30 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book 3D Face Recognition Using PCA written by Yagnesh Parmar and published by LAP Lambert Academic Publishing. This book was released on 2012-04 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book 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 depth-values 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 images.

Download or read book Face Recognition in Adverse Conditions written by De Marsico, Maria and published by IGI Global. This book was released on 2014-04-30 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Facial recognition software has improved by leaps and bounds over the past few decades, with error rates decreasing significantly within the past ten years. Though this is true, conditions such as poor lighting, obstructions, and profile-only angles have continued to persist in preventing wholly accurate readings. Face Recognition in Adverse Conditions examines how the field of facial recognition takes these adverse conditions into account when designing more effective applications by discussing facial recognition under real world PIE variations, current applications, and the future of the field of facial recognition research. The work is intended for academics, engineers, and researchers specializing in the field of facial recognition.

Download or read book Face Recognition written by S. Ramakrishnan and published by BoD – Books on Demand. This book was released on 2016-07-06 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern recognition has gained significant attention due to the rapid explosion of internet- and mobile-based applications. Among the various pattern recognition applications, face recognition is always being the center of attraction. With so much of unlabeled face images being captured and made available on internet (particularly on social media), conventional supervised means of classifying face images become challenging. This clearly warrants for semi-supervised classification and subspace projection. Another important concern in face recognition system is the proper and stringent evaluation of its capability. This book is edited keeping all these factors in mind. This book is composed of five chapters covering introduction, overview, semi-supervised classification, subspace projection, and evaluation techniques.

Download or read book Human Face Verification by Robust 3D Surface Alignment written by Dirk Joel Luchini Colbry and published by . This book was released on 2006 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Robust Image Based 3D Face Recognition written by Wenyi Zhao and published by . This book was released on 1999 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical pattern recognition and computer vision techniques have been successfully applied to many object recognition problems. One typical example is the task of face recognition where a 3D face object may appear dramatically different under different lighting or viewing conditions. In this thesis, we propose combining pattern recognition and computer vision methods for robust face recognition. The first part of this thesis deals with statistical pattern recognition approaches. Many classifiers such as the Bayesian classifier (theoretically optimal) and nearest-neighbor rule are available. For applications involving high-dimensional patterns such as faces, the demand for a large number of training samples to construct a good Bayesian classifier is difficult to satisfy. In this thesis we propose a statistical framework, subspace discriminant analysis, using which we can construct good classifiers (both linear and nonlinear) using only limited numbers of training samples. To construct generalizable features for face recognition, a face subspace is constructed. This is motivated by the observation that face recognition is primarily about distinguishing among similar objects --- faces. A detailed description of subspace LDA/DCA is presented along with extensive experimental results including FERET tests. The second part of this thesis deals with taking a computer vision approach to robust object recognition. First, we develop a new shape-from-shading (SFS) theory called symmetric SFS (SSFS) to handle symmetric objects such as faces. One big advantage of SSFS is that we have shown that SSFS not only has a point-wise unique solution for the partial derivatives of the depth map but also a unique solution for albedo. Next for the specific task of face recognition, we propose using SSFS and a generic 3D face model to address the illumination problem and demonstrate significant performance improvement. Finally the problem of pose variation coupled with illumination change in face recognition is addressed. This method is based on a new view synthesis technique. Experimental results using several commonly available databases are reported.

Download or read book Amyotrophic Lateral Sclerosis Among Guamanians in California written by Jose M. Torres and published by . This book was released on 1957 with total page 4 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Advanced Concepts for Intelligent Vision Systems written by Wilfried Philips and published by Springer. This book was released on 2009-09-30 with total page 760 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2009, held in Bordeaux, France in September/October 2009. The 43 revised full papers and 25 posters presented were carefully reviewed and selected from 115 submissions. The papers are organized in topical sections on technovision, fundamental mathematical techniques, image processing, coding and filtering, image and video analysis, computer vision, tracking, color, multispectral and special-purpose imaging, medical imaging, and biometrics.

Download or read book 3D Integral Invariant Signatures And Their Application on Face Recognition written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Curves are important features in computer vision and pattern recognition, and their classification under a variety of transformations, such as Euclidean, affine or projective, poses a great challenge. Invariant features of these curves turn out to be crucial to simplifying any classification procedure. This, as a result, has recently led to a renewed research interest in transformation invariants. In this thesis, new explicit formulae for integral invariants for curves in 3D with respect to the special and the full affine groups are presented. The development of the 3D integral invariant are based on an inductive approach in terms of Euclidean invariants. For the first time, a clear geometric interpretation of both 2D and 3D integral invariants is presented. Since integration attenuates the effects of noise, integral invariants have advantages in computer vision applications. We use integral invariants to construct global and local signatures that characterize curves up to the special affine transformations, subsequently extended to the full affine group. Global Signatures are independent of parameterization, and Local Signatures are independent of both parameterizationa and initial point selection. We analyze the robustness of these invariants in their application to the problem of classification of noisy spatial curves extracted as characteristics from a 3D object. Our investigation of 2D and 3D integral invariants and signatures, originally motivated by Biometrics applications, are successfully implemented and applied to face recognition to eliminate the effects of pose and facial expression. A high recognition performance rate of 95% is achieved in the test with a large face data set.

Download or read book Reliable Face Recognition Methods written by Harry Wechsler and published by Springer Science & Business Media. This book was released on 2009-04-05 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book seeks to comprehensively address the face recognition problem while gaining new insights from complementary fields of endeavor. These include neurosciences, statistics, signal and image processing, computer vision, machine learning and data mining. The book examines the evolution of research surrounding the field to date, explores new directions, and offers specific guidance on the most promising venues for future research and development. The book’s focused approach and its clarity of presentation make this an excellent reference work.

Download or read book Biometrics and ID Management written by Claus Vielhauer and published by Springer Science & Business Media. This book was released on 2011-03 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the COST 2101 International Workshop, BIOID 2011, held in Brandenburg (Havel), Germany, in March 2011. The 25 revised full papers presented were carefully reviewed and selected from numerous submissions and are completed by an introduction on COST. The papers are organized in topical main sections on theory and systems, handwriting authentication, speaker authentication, face recognition, multibiometric authentication, and on biometrics and forensics.

Download or read book Biometric Recognition written by Zhenan Sun and published by Springer. This book was released on 2014-10-29 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th Chinese Conference on Biometric Recognition, CCBR 2014, held in Shenyang, China, in November 2014. The 60 revised full papers presented were carefully reviewed and selected from among 90 submissions. The papers focus on face, fingerprint and palmprint, vein biometrics, iris and ocular biometrics, behavioral biometrics, application and system of biometrics, multi-biometrics and information fusion, other biometric recognition and processing.

Download or read book Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition Analysis and Image Processing written by Kamila, Narendra Kumar and published by IGI Global. This book was released on 2015-11-30 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: ###############################################################################################################################################################################################################################################################