Tesis sobre el tema "3D face analysi"
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Amin, Syed Hassan. "Analysis of 3D face reconstruction". Thesis, Imperial College London, 2009. http://hdl.handle.net/10044/1/6163.
Texto completoLee, Jinho. "Synthesis and analysis of human faces using multi-view, multi-illumination image ensembles". Columbus, Ohio : Ohio State University, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1133366279.
Texto completoHu, Guosheng. "Face analysis using 3D morphable models". Thesis, University of Surrey, 2015. http://epubs.surrey.ac.uk/808011/.
Texto completoWei, Xiaozhou. "3D facial expression modeling and analysis with topographic information". Diss., Online access via UMI:, 2008.
Buscar texto completoWang, Jing. "Reconstruction and Analysis of 3D Individualized Facial Expressions". Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32588.
Texto completoClement, Stephen J. "Sparse shape modelling for 3D face analysis". Thesis, University of York, 2014. http://etheses.whiterose.ac.uk/8248/.
Texto completoZhao, Xi. "3D face analysis : landmarking, expression recognition and beyond". Phd thesis, Ecole Centrale de Lyon, 2010. http://tel.archives-ouvertes.fr/tel-00599660.
Texto completoSzeptycki, Przemyslaw. "Processing and analysis of 2.5D face models for non-rigid mapping based face recognition using differential geometry tools". Phd thesis, Ecole Centrale de Lyon, 2011. http://tel.archives-ouvertes.fr/tel-00675988.
Texto completoHariri, Walid. "Contribution à la reconnaissance/authentification de visages 2D/3D". Thesis, Cergy-Pontoise, 2017. http://www.theses.fr/2017CERG0905/document.
Texto completo3D face analysis including 3D face recognition and 3D Facial expression recognition has become a very active area of research in recent years. Various methods using 2D image analysis have been presented to tackle these problems. 2D image-based methods are inherently limited by variability in imaging factors such as illumination and pose. The recent development of 3D acquisition sensors has made 3D data more and more available. Such data is relatively invariant to illumination and pose, but it is still sensitive to expression variation. The principal objective of this thesis is to propose efficient methods for 3D face recognition/verification and 3D facial expression recognition. First, a new covariance based method for 3D face recognition is presented. Our method includes the following steps : first 3D facial surface is preprocessed and aligned. A uniform sampling is then applied to localize a set of feature points, around each point, we extract a matrix as local region descriptor. Two matching strategies are then proposed, and various distances (geodesic and non-geodesic) are applied to compare faces. The proposed method is assessed on three datasetsincluding GAVAB, FRGCv2 and BU-3DFE. A hierarchical description using three levels of covariances is then proposed and validated. In the second part of this thesis, we present an efficient approach for 3D facial expression recognition using kernel methods with covariance matrices. In this contribution, we propose to use Gaussian kernel which maps covariance matrices into a high dimensional Hilbert space. This enables to use conventional algorithms developed for Euclidean valued data such as SVM on such non-linear valued data. The proposed method have been assessed on two known datasets including BU-3DFE and Bosphorus datasets to recognize the six prototypical expressions
McCool, Christopher Steven. "Hybrid 2D and 3D face verification". Thesis, Queensland University of Technology, 2007. https://eprints.qut.edu.au/16436/1/Christopher_McCool_Thesis.pdf.
Texto completoMcCool, Christopher Steven. "Hybrid 2D and 3D face verification". Queensland University of Technology, 2007. http://eprints.qut.edu.au/16436/.
Texto completoDrira, Hassen. "Statistical computing on manifolds for 3D face analysis and recognition". Thesis, Lille 1, 2011. http://www.theses.fr/2011LIL10075/document.
Texto completoAutomatic face recognition has many benefits over other biometric technologies due to the natural, non-intrusive, and high throughput nature of face data acquisition. Thus, the techniques for face recognition have received a growing attention within the computer vision community over the past three decades. In terms of a modality for face imaging, a major advantage of 3D scans over 2D color imaging is that variations in illumination and scaling have less influence on the 3D scans.However, scan data often suffer from the problem of missing parts dueto self-occlusions or imperfections in scanning technologies. Additionally, variations in face data due to facial expressions are challenging to 3D face recognition. In order to be useful in real-world applications, 3D face recognition approaches should be able to successfully recognize face scans even in the presence of large expression-based deformations and missing data due to occlusions and pose variation. Most recent research has been directed towards expression-invariant techniques and spent less effort to handle the missing parts problem. Few approaches handles the missing part problem but none has performed on a full database containing real missing data, they simulate some missing parts. We present a common framework handling both large expressions and missing parts due to large pose variation. In addition, with the same framework, we are able to average surfaces and hierarchically organize databases to allow efficient searches. In presence of occlusion, we propose to delete and restore occluded parts. The surface is first represented by radial curves (emanating from the nose tip fo the 3D face). Then a base is built using PCA for each curve. Hence, the missing part of the curve can be restored by projecting the existing part of it on the base. PCA is applied on the tangent space of the mean curve as it is linear space. Once the occlusion was detected and removed, the occlusion challenge can be handled as a missing data problem. Hence, we apply the restoration framework and then apply our radial-curve-based 3D face recognition algorithm
Dagnes, Nicole. "3D human face analysis for recognition applications and motion capture". Thesis, Compiègne, 2020. http://www.theses.fr/2020COMP2542.
Texto completoThis thesis is intended as a geometrical study of the three-dimensional facial surface, whose aim is to provide an application framework of entities coming from Differential Geometry context to use as facial descriptors in face analysis applications, like FR and FER fields. Indeed, although every visage is unique, all faces are similar and their morphological features are the same for all mankind. Hence, it is primary for face analysis to extract suitable features. All the facial features, proposed in this study, are based only on the geometrical properties of the facial surface. Then, these geometrical descriptors and the related entities proposed have been applied in the description of facial surface in pattern recognition contexts. Indeed, the final goal of this research is to prove that Differential Geometry is a comprehensive tool oriented to face analysis and geometrical features are suitable to describe and compare faces and, generally, to extract relevant information for human face analysis in different practical application fields. Finally, since in the last decades face analysis has gained great attention also for clinical application, this work focuses on musculoskeletal disorders analysis by proposing an objective quantification of facial movements for helping maxillofacial surgery and facial motion rehabilitation. At this time, different methods are employed for evaluating facial muscles function. This research work investigates the 3D motion capture system, adopting the Technology, Sport and Health platform, located in the Innovation Centre of the University of Technology of Compiègne, in the Biomechanics and Bioengineering Laboratory (BMBI)
Alashkar, Taleb. "3D dynamic facial sequences analysis for face recognition and emotion detection". Thesis, Lille 1, 2015. http://www.theses.fr/2015LIL10109/document.
Texto completoIn this thesis, we have investigated the problems of identity recognition and emotion detection from facial 3D shapes animations (called 4D faces). In particular, we have studied the role of facial (shapes) dynamics in revealing the human identity and their exhibited spontaneous emotion. To this end, we have adopted a comprehensive geometric framework for the purpose of analyzing 3D faces and their dynamics across time. That is, a sequence of 3D faces is first split to an indexed collection of short-term sub-sequences that are represented as matrix (subspace) which define a special matrix manifold called, Grassmann manifold (set of k-dimensional linear subspaces). The geometry of the underlying space is used to effectively compare the 3D sub-sequences, compute statistical summaries (e.g. sample mean, etc.) and quantify densely the divergence between subspaces. Two different representations have been proposed to address the problems of face recognition and emotion detection. They are respectively (1) a dictionary (of subspaces) representation associated to Dictionary Learning and Sparse Coding techniques and (2) a time-parameterized curve (trajectory) representation on the underlying space associated with the Structured-Output SVM classifier for early emotion detection. Experimental evaluations conducted on publicly available BU-4DFE, BU4D-Spontaneous and Cam3D Kinect datasets illustrate the effectiveness of these representations and the algorithmic solutions for identity recognition and emotion detection proposed in this thesis
Aljarrah, Inad A. "Three Dimensional Face Recognition Using Two Dimensional Principal Component Analysis". Ohio University / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1142453613.
Texto completoGevaux, Lou. "3D-hyperspectral imaging and optical analysis of skin for the human face". Thesis, Lyon, 2019. http://www.theses.fr/2019LYSES035.
Texto completoHyperspectral imaging (HSI), a non-invasive, in vivo imaging method that can be applied to measure skin spectral reflectance, has shown great potential for the analysis of skin optical properties on small, flat areas: by combining a skin model, a model of light-skin interaction and an optimization algorithm, an estimation of skin chromophore concentration in each pixel of the image can be obtained, corresponding to quantities such as melanin and blood. The purpose of this work is to extend this method to large, non-flat areas, in particular the human face. The accurate measurement of complex objects such as the face must account for variances of illumination that result from the 3D geometry of an object, which we call irradiance drifts. Unless they are accounted for, irradiance drifts will lead to errors in the hyperspectral image analysis.In the first part of the work, we propose a measurement setup comprising a wide field HSI camera (with an acquisition range of 400 - 700 nm, in 10 nm width wavebands) and a 3D measurement system using fringe projection. As short acquisition time is crucial for in vivo measurement, a trade-off between resolution and speed has been made so that the acquisition time remains under 5 seconds.To account for irradiance drifts, a correction method using the surface 3D geometry and radiometry principles is proposed. The irradiance received on the face is computed for each pixel of the image, and the resulting data used to suppress the irradiance drifts in the measured hyperspectral image. This acts as a pre-processing step to be applied before image analysis. This method, however, failed to yield satisfactory results on those parts of the face almost perpendicular to the optical axis of the camera, such as the sides of the nose, and was therefore discarded in favor of using an optimization algorithm robust to irradiance drifts in the analysis method.Skin analysis from the measured hyperspectral image is performed using optical models and an optimization method. Skin is modeled as a two-layer translucent material whose absorption and scattering properties are determined by its composition in chromophores. Light-skin interactions are modeled using a two-flux method. An inverse problem is solved by optimization to retrieve information about skin composition from the measured reflectance. The chosen optical models represent a trade-off between accuracy and acceptable computation time, which increases exponentially with the number of parameters in the model. The resulting chromophore maps can be added to the 3D mesh measured using the 3D-HSI camera for display purposes.In the spectral reflectance analysis method, skin scattering properties are assumed to be the same for everyone and on every part of the body, which represents a shortcoming. In the second part of this work, the fringe projector originally intended for measuring 3D geometry is used to acquire skin modulation transfer function (MTF), a quantity that yields information about both skin absorption and scattering coefficients. The MTF is measured using spatial frequency domain imaging (SFDI) and analyzed by an optical model relying on the diffusion equation to estimate skin scattering coefficients. On non-flat objects, retrieving such information independently from irradiance drifts is a significant challenge. The novelty of the proposed method is that it combines HSI and SFDI to obtain skin scattering coefficient maps of the face independently from its shape.We emphasize throughout this dissertation the importance of short acquisition time for in vivo measurement. The HSI analysis method, however, is extremely time-consuming, preventing real time image analysis. A preliminary attempt to address this shortcoming is presented, using neural networks to replace optimization-based analysis. Initial results of the method have been promising, and could drastically reduce calculation time from around an hour to a second
Wang, Xianwang. "Single View Reconstruction for Human Face and Motion with Priors". UKnowledge, 2010. http://uknowledge.uky.edu/gradschool_diss/62.
Texto completoHan, Xia. "Towards the Development of an Efficient Integrated 3D Face Recognition System. Enhanced Face Recognition Based on Techniques Relating to Curvature Analysis, Gender Classification and Facial Expressions". Thesis, University of Bradford, 2011. http://hdl.handle.net/10454/5347.
Texto completoStrand, Robin. "Distance Functions and Image Processing on Point-Lattices : with focus on the 3D face- and body-centered cubic grids". Doctoral thesis, Uppsala universitet, Centrum för bildanalys, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-9312.
Texto completoBolkart, Timo [Verfasser] y Stefanie [Akademischer Betreuer] Wuhrer. "Dynamic and groupwise statistical analysis of 3D faces / Timo Bolkart. Betreuer: Stefanie Wuhrer". Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2016. http://d-nb.info/1104733293/34.
Texto completoDerkach, Dmytro. "Spectrum analysis methods for 3D facial expression recognition and head pose estimation". Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/664578.
Texto completoFacial analysis has attracted considerable research efforts over the last decades, with a growing interest in improving the interaction and cooperation between people and computers. This makes it necessary that automatic systems are able to react to things such as the head movements of a user or his/her emotions. Further, this should be done accurately and in unconstrained environments, which highlights the need for algorithms that can take full advantage of 3D data. These systems could be useful in multiple domains such as human-computer interaction, tutoring, interviewing, health-care, marketing etc. In this thesis, we focus on two aspects of facial analysis: expression recognition and head pose estimation. In both cases, we specifically target the use of 3D data and present contributions that aim to identify meaningful representations of the facial geometry based on spectral decomposition methods: 1. We propose a spectral representation framework for facial expression recognition using exclusively 3D geometry, which allows a complete description of the underlying surface that can be further tuned to the desired level of detail. It is based on the decomposition of local surface patches in their spatial frequency components, much like a Fourier transform, which are related to intrinsic characteristics of the surface. We propose the use of Graph Laplacian Features (GLFs), which result from the projection of local surface patches into a common basis obtained from the Graph Laplacian eigenspace. The proposed approach is tested in terms of expression and Action Unit recognition and results confirm that the proposed GLFs produce state-of-the-art recognition rates. 2. We propose an approach for head pose estimation that allows modeling the underlying manifold that results from general rotations in 3D. We start by building a fully-automatic system based on the combination of landmark detection and dictionary-based features, which obtained the best results in the FG2017 Head Pose Estimation Challenge. Then, we use tensor representation and higher order singular value decomposition to separate the subspaces that correspond to each rotation factor and show that each of them has a clear structure that can be modeled with trigonometric functions. Such representation provides a deep understanding of data behavior, and can be used to further improve the estimation of the head pose angles.
Fernandez-Abrevaya, Victoria. "Apprentissage à grande échelle de modèles de formes et de mouvements pour le visage 3D". Electronic Thesis or Diss., Université Grenoble Alpes, 2020. https://theses.hal.science/tel-03151303.
Texto completoData-driven models of the 3D face are a promising direction for capturing the subtle complexities of the human face, and a central component to numerous applications thanks to their ability to simplify complex tasks. Most data-driven approaches to date were built from either a relatively limited number of samples or by synthetic data augmentation, mainly because of the difficulty in obtaining large-scale and accurate 3D scans of the face. Yet, there is a substantial amount of information that can be gathered when considering publicly available sources that have been captured over the last decade, whose combination can potentially bring forward more powerful models.This thesis proposes novel methods for building data-driven models of the 3D face geometry, and investigates whether improved performances can be obtained by learning from large and varied datasets of 3D facial scans. In order to make efficient use of a large number of training samples we develop novel deep learning techniques designed to effectively handle three-dimensional face data. We focus on several aspects that influence the geometry of the face: its shape components including fine details, its motion components such as expression, and the interaction between these two subspaces.We develop in particular two approaches for building generative models that decouple the latent space according to natural sources of variation, e.g.identity and expression. The first approach considers a novel deep autoencoder architecture that allows to learn a multilinear model without requiring the training data to be assembled as a complete tensor. We next propose a novel non-linear model based on adversarial training that further improves the decoupling capacity. This is enabled by a new 3D-2D architecture combining a 3D generator with a 2D discriminator, where both domains are bridged by a geometry mapping layer.As a necessary prerequisite for building data-driven models, we also address the problem of registering a large number of 3D facial scans in motion. We propose an approach that can efficiently and automatically handle a variety of sequences while making minimal assumptions on the input data. This is achieved by the use of a spatiotemporal model as well as a regression-based initialization, and we show that we can obtain accurate registrations in an efficient and scalable manner.Finally, we address the problem of recovering surface normals from natural images, with the goal of enriching existing coarse 3D reconstructions. We propose a method that can leverage all available image and normal data, whether paired or not, thanks to a new cross-modal learning architecture. Core to our approach is a novel module that we call deactivable skip connections, which allows to transfer the local details from the image to the output surface without hurting the performance when autoencoding modalities, achieving state-of-the-art results for the task
Schurch, Brandt Roger. "Three-dimensional imaging and analysis of electrical trees". Thesis, University of Manchester, 2014. https://www.research.manchester.ac.uk/portal/en/theses/threedimensional-imaging-and-analysis-of-electrical-trees(73e032f6-3e6b-4ee9-9cc1-953a11f36cb3).html.
Texto completoAkilo, Michele Arinze. "design and analysis of a composite panel with ultra-thin glass faces and a 3d–printed polymeric core". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/15351/.
Texto completoAssali, Pierre. "Modélisation géostructurale 3D de parois rocheuses en milieu ferroviaire : application aux ouvrages en terre". Thesis, Strasbourg, 2014. http://www.theses.fr/2014STRAD009.
Texto completoThis project aims at an optimization of geostructural modeling methodolgies, leading to a better knowledge and a better management of the rock risk impacting the railway system. Acquired 3D models are exploited in order ton convert 3D point clouds into geostructural analysis. Hence, we have developed a semi-automatic process that allows 3D models to be combined with the results of field surveys in order to provide more precise analyses of rock faces, for example, by classifying rock discontinuities into subsets according to their orientation. A second approach is proposed, combining both 3D point clouds (from LiDAR or image matching) and 2D digital images. Combining these high-quality data with the proposed automatic and manual processing method greatly improves the geometrical analysis of rock faces, increases the reliability of structural interpretations, and enables reinforcement procedures to be optimized
Bonomi, Mattia. "Facial-based Analysis Tools: Engagement Measurements and Forensics Applications". Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/271342.
Texto completoBonomi, Mattia. "Facial-based Analysis Tools: Engagement Measurements and Forensics Applications". Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/271342.
Texto completoKim, Leejin. "Analysis and Construction of Engaging Facial Forms and Expressions: Interdisciplinary Approaches from Art, Anatomy, Engineering, Cultural Studies, and Psychology". VCU Scholars Compass, 2013. http://scholarscompass.vcu.edu/etd/567.
Texto completoCacchi, Alberto. "Analisi di sensibilità per la valutazione di driver aritmici con catetere ad alta risoluzione". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22987/.
Texto completo"Automatic segmentation and registration techniques for 3D face recognition". Thesis, 2008. http://library.cuhk.edu.hk/record=b6074674.
Texto completoThen we propose a fully automatic registration method that can handle facial expressions with high accuracy and robustness for 3D face image alignment. In our method, the nose region, which is relatively more rigid than other facial regions in the anatomical sense, is automatically located and analyzed for computing the precise location of a symmetry plane. Extensive experiments have been conducted using the FRGC (V1.0 and V2.0) benchmark 3D face dataset to evaluate the accuracy and robustness of our registration method. Firstly, we compare its results with two other registration methods. One of these methods employs manually marked points on visualized face data and the other is based on the use of a symmetry plane analysis obtained from the whole face region. Secondly, we combine the registration method with other face recognition modules and apply them in both face identification and verification scenarios. Experimental results show that our approach performs better than the other two methods. For example, 97.55% Rank-1 identification rate and 2.25% EER score are obtained by using our method for registration and the PCA method for matching on the FRGC V1.0 dataset. All these results are the highest scores ever reported using the PCA method applied to similar datasets.
We firstly propose an automatic 3D face segmentation method. This method is based on deep understanding of 3D face image. Concepts of proportions of the facial and nose regions are acquired from anthropometrics for locating such regions. We evaluate this segmentation method on the FRGC dataset, and obtain a success rate as high as 98.87% on nose tip detection. Compared with results reported by other researchers in the literature, our method yields the highest score.
Tang, Xinmin.
Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3616.
Thesis (Ph.D.)--Chinese University of Hong Kong, 2008.
Includes bibliographical references (leaves 109-117).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstracts in English and Chinese.
School code: 1307.
Barbosa, Rui Filipe de Arvins. "Accuracy Analysis of Region-Based 2D and 3D Face Recognition - Comparasion of Nasal and Mask-Wearing Ocular Regions". Master's thesis, 2020. http://hdl.handle.net/10316/93944.
Texto completoA evolução dos sistemas de FR que tem ocorrido recentemente foi em grande parte consequência da evolução da tecnologia disponível, permitindo incluir novas analises 3D combinadas com os métodos 2D já desenvolvidos para sistemas de FR, aliado ao desenvolvimento e melhoramento de novos algoritmos de machinelearning.Apesar das ultimas conquistas dos sistemas de FR, recentes mudanças de hábitos, como a generalização da utilização da máscara como consequência da pandemia de COVID-19, representam um novo desafio para os algoritmos de FR. A maioria dos metodos não foi testada nesta nova realidade, tornando um estudo atualizado sobre FR fundamental para entender se poderão ser reutilizados ou encontram-se obsoletos.Neste trabalho um modelo classico de deteção de features desenvolvido por Emambakhsh & Evans et al. [1], baseado em patches nasais esfericos que combinados com uma NN projetada e personalizada e projetado, com o objetivo de analisar possíveis aplicações sobre uma populacão multicultural e diversificada, como foi proposto pelo artigo.Para adequar a tese a nova realidade, foram realizados testes para comprovarque algoritmos focados na regiao ocular alcançam valores de sucesso semelhantes quando comparados com a regiao nasal de forma a superar a oclusão da mesma como consequencia da utilização de mascara devido à pandemia COVID. Uma segunda versao do sistema FR inicialmente implementado para demonstrar o primeiro objetivo foi projetada tendo sido demonstrado que estes efetivamente mantem uma precisao comparável no domínio 3D.
The evolution of Facial Recognition (FR) systems that has occurred in recenttimes was largely consequence of the evolution in the available technology allowing to include new 3 dimensions analysis combined with the 2 dimensions methodsalready developed in FR systems, combined with the development of new and improved machine learning algorithms.Despite FR systems latter achievements, recent habits changes such as the generalization of face covering, as a consequence of COVID-19 pandemic present anew challenge to FR algorithms. The majority of the methods have not been testedin this new reality making an updated survey over FR fundamental to understand ifthey can be reused or appear obsolete.In this work a classic feature extractor algorithm developed by Emambakhsh & Evans et al. [1] based on spherical patches working combined with a designed and personalized Neural Network (NN) is applied with the objective to demonstrate the importance of the nasal region for 3D FR algorithms, as stated in the article.In order to adapt the research to a new reality, tests were preformed to prove thatalgorithms focused on the ocular region reach similar values of success when compared with the nasal region in order to overcome the nose occlusion consequence of using face coverings due to the COVID pandemic. A second version of the FR system built for the first objective demonstration was implemented having been demonstrated that these effectively have comparable accuracy in the 3D domain. .
Jin-an, Jiang y 江金安. "The Computer System Development For Tunnel Face Image Analysis and 3D Display". Thesis, 2000. http://ndltd.ncl.edu.tw/handle/77791260701962768658.
Texto completo國立臺灣科技大學
營建工程系
88
The“NATM”, an excavation method of rock tunnel, is popularly used at the present time. The traditional method of geology record is recorded in the tunnel site by the geologist or the experienced engineers. It is unavoidable to leave out or misjudge that they record the geological conditions in a short time by naked eyes, and to draw a sectional or expanding drawing will be difficult and waste lots of time. Furthermore, the 2D drawing is inconceivable to a real 3D space. For this reason, the purpose of this study is to develop a computer system named “Tunnel Face Image Analysis and 3D Display System”. Continuous tunnel face images in the tunnel site are filmed and stacked by using the technology of 3D display to show the orientation of weak planes, including strike and dip. The computer system was developed using Borland C++ Builder 5.0, 3D display software “Slicer Dicer” and Microsoft Access 97. It can improve the traditional geological recording and is advantageous to the information communication and feedback. The functions of image preprocessing, including enhancement and segmentation, enhance the weak planes and extract them from image. Image interpolation is made between two rounds. 3D images are reconstructed to show the orientation of weak planes, including strike and dip. The 3D visual effect will help us realize the geological condition more easily and clearly.
MASI, IACOPO. "From motion to faces: 3D-assisted automatic analysis of people". Doctoral thesis, 2014. http://hdl.handle.net/2158/853304.
Texto completoMohammadzade, Narges Hoda. "Two- and Three-dimensional Face Recognition under Expression Variation". Thesis, 2012. http://hdl.handle.net/1807/32773.
Texto completoVilla, C., Jo Buckberry, C. Cattaneo, B. Frohlich y N. Lynnerup. "Quantitative analysis of the morphological changes of the pubic symphyseal face and the auricular surface and implications for age at death estimation". 2015. http://hdl.handle.net/10454/7176.
Texto completoAge estimation methods are often based on the age-related morphological changes of the auricular surface and the pubic bone. In this study, a mathematical approach to quantify these changes has been tested analyzing the curvature variation on 3D models from CT and laser scans. The sample consisted of the 24 Suchey–Brooks (SB) pubic bone casts, 19 auricular surfaces from the Buckberry and Chamberlain (BC) “recording kit” and 98 pelvic bones from the Terry Collection (Smithsonian Institution). Strong and moderate correlations between phases and curvature were found in SB casts (ρ 0.60–0.93) and BC “recording kit” (ρ 0.47–0.75), moderate and weak correlations in the Terry Collection bones (pubic bones: ρ 0.29–0.51, auricular surfaces: ρ 0.33–0.50) but associated with large individual variability and overlap of curvature values between adjacent decades. The new procedure, requiring no expert judgment from the operator, achieved similar correlations that can be found in the classic methods.