The following work explores the role of 3D printing in biological anthropology. A case study approach is used to provide an understanding of two different applications for 3D printing and to identify a potential methodology for creating 3D models. Case study one looks at the application of 3D printing to reconstruction projects using a flowerpot to test the reconstruction methodology. The second case study uses both laser surface and CT scanning to create a replica of a human skeleton. The two methods of data acquisition are evaluated for advantages and limitations in creating the virtual model. This work shows that there is a role for 3D printing in biological anthropology, but that data acquisition and processing issues are the most significant limiting factors in producing skeletal replicas. / October 2006

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The following work explores the role of 3D printing in biological anthropology. A case study approach is used to provide an understanding of two different applications for 3D printing and to identify a potential methodology for creating 3D models. Case study one looks at the application of 3D printing to reconstruction projects using a flowerpot to test the reconstruction methodology. The second case study uses both laser surface and CT scanning to create a replica of a human skeleton. The two methods of data acquisition are evaluated for advantages and limitations in creating the virtual model. This work shows that there is a role for 3D printing in biological anthropology, but that data acquisition and processing issues are the most significant limiting factors in producing skeletal replicas.

The objective of this study was to: (1) model the course of the lingual nerve (LN) in the third molar region using digitized data and (2) investigate landmarks to aid in predicting the position of LN. A MicroScribe 3-DX digitizer and Autodesk® Maya® 8.5 were used to create 3-D in-situ models of LN for seven human cadaveric specimens. Regression analysis demonstrated that an anteriorly positioned lingula is directly proportional to the vertical distance of the LN relative to the alveolar crest (p < 0.05). A superiorly positioned mylohyoid ridge was also directly proportional to the vertical distance of the LN relative to the alveolar crest (p < 0.05). The LN is positioned closer to the alveolar crest in specimens where the mylohyoid ridge is positioned superiorly (p = 0.001). This study demonstrated a novel way of quantifying the relative position of the LN using 3-D computer modeling.

The objective of this study was to: (1) model the course of the lingual nerve (LN) in the third molar region using digitized data and (2) investigate landmarks to aid in predicting the position of LN. A MicroScribe 3-DX digitizer and Autodesk® Maya® 8.5 were used to create 3-D in-situ models of LN for seven human cadaveric specimens. Regression analysis demonstrated that an anteriorly positioned lingula is directly proportional to the vertical distance of the LN relative to the alveolar crest (p < 0.05). A superiorly positioned mylohyoid ridge was also directly proportional to the vertical distance of the LN relative to the alveolar crest (p < 0.05). The LN is positioned closer to the alveolar crest in specimens where the mylohyoid ridge is positioned superiorly (p = 0.001). This study demonstrated a novel way of quantifying the relative position of the LN using 3-D computer modeling.

This thesis deals with quantifying the merits of Distributed Maximum Power Point Tracking (DMPPT), as well as providing solutions to achieve DMPPT in PV systems. A general method based on 3D modeling is developed to determine the energy yield of PV installations exploiting different levels of DMPPT granularity. Sub-string-level DMPPT is shown to have up to 30% more annual energy yield than panel-level DMPPT. A Multi-Input-Single-Output (MISO) dc-dc converter is proposed to achieve DMPPT in parallel-connected applications. A digital current-mode controller is used to operate the MISO converter in pseudo-CCM mode. For series-connected applications, the virtualparallel concept is introduced to utilize the robustness of the parallel connection. This concept is demonstrated on a three-phase boost converter. The topology offers reduced output voltage ripple under shading which increases the life-time of the output capacitor. The prototypes yield output power benefits of up to 46% and 20% for the tested shading conditions.

The following work explores the role of 3D printing in biological anthropology. A case study approach is used to provide an understanding of two different applications for 3D printing and to identify a potential methodology for creating 3D models. Case study one looks at the application of 3D printing to reconstruction projects using a flowerpot to test the reconstruction methodology. The second case study uses both laser surface and CT scanning to create a replica of a human skeleton. The two methods of data acquisition are evaluated for advantages and limitations in creating the virtual model. This work shows that there is a role for 3D printing in biological anthropology, but that data acquisition and processing issues are the most significant limiting factors in producing skeletal replicas.

L'évolution biologique des organismes peut être étudiée comme une succession de transformations morphologiques qui sont caractérisées par le changement de leur géométrie tridimensionnelle globale et locale. Dans ce contexte, il est nécessaire de développer des outils mathématiques et informatiques comparatifs de formes tridimensionnelles afin d'étudier ces transformations et de pouvoir les comparer avec les variabilités inter- et intra-espèces. Dans la chaîne de traitement des données tridimensionnelles (images 3D ou maillages 3D) employée en " paléoanthropologie virtuelle ", la méthode la plus souvent utilisée en analyse comparative est basée sur des points de repère (en général, anatomiques) dont les coordonnées sont analysées à l'aide d'outils mathématiques tels que la " morphométrie géométrique ". Plus récemment, une autre classe de méthodes a été proposée. Elle permet des comparaisons globales entre les surfaces complètes de structures anatomiques sans avoir besoin de définir des points de repère. On obtient ainsi une analyse statistique de la forme moyenne et de sa variabilité en tout point. Dans cette thèse, nous proposons d'étudier la chaîne d'analyse morphométrique des données 3D utilisées en paléoanthropologie, de la numérisation à l'exploitation des données par les chercheurs. Cette thèse présente des méthodes analytiques pour le traitement des données issues de la paléoanthropologie, depuis la numérisation des sites de fouilles jusqu'à l'acquisition et l'analyse des spécimens. Nous établissons des modèles numériques de terrain (analyses multidimensionnelles de données issues de différentes modalités d'acquisition telles que les scans laser et la photogrammétrie) qui permettent d'appréhender les vestiges dans leur contexte et nous proposons des analyses qui répondent à des problématiques qui sont spécifiques aux études en biologie. En particulier, nous apportons des outils d'analyse et de visualisation (cartographies 3D et analyses statistiques) pour des problématiques de déformation basées sur des recalages surfaciques. Nous proposons également une méthode d'analyse sur des données partielles afin de pouvoir exploiter l'ensemble des données disponibles dans les registres fossiles et modernes. Nos résultats mettent en évidence que les méthodes par recalage surfacique augmentent non seulement les possibilités de capter les formes et leurs variations, mais permettent également de travailler sur des formes globales et non uniquement sur certains points. Nous montrons notamment que ces méthodes permettent le développement d'outils qui sont bien adaptés pour les études en paléoanthropologie. / The biological evolution of organisms can be studied as a set of morphological transformations which are characterized by the modification of their global three- dimensional geometry and by some discrete traits. In this context, it is necessary to develop comparative mathematical and computational tools for the study of the inter- and intraspecific variation. Within the three-dimensional data processing workflow (3D images or 3D meshes) employed in " virtual paleoanthropology ", the method that is most commonly used in comparative analysis is based on landmarks (most often anatomical landmarks) from which coordinates are analyzed by using mathematical tools such as " geometric morphometrics ". More recently, other methods allowing global comparisons between three-dimensional reconstructions without landmarks have been proposed. They allow for example the statistical analysis of a global shape and its variability. We suggest to study the process for morphometric analysis of 3D data commonly used in paleoanthropology, from the digitization to the exploration of 3D data. This dissertation introduces analytical methods for the processing of data provided by paleoanthropological studies, from the digitization of the excavation sites to the acquisition and the analysis of specimens. We established digital ground models (multidimensional analyses of data from various modalities of acquisition such as laser scanner and photogrammetry) that contribute to a comprehensive understanding of fossil remains in their context and we proposed relevant analyses for resolving specific problems inherent to biological studies. In particular, we developed appropriate tools for analyses and viewing (3D mappings and statistical analyses) dedicated specifically to problems of deformation-based registrations. Additionally, we introduced a method for the analysis of partial data in order to use all the specimens available in the fossil and modern records. Besides opening up new possibilities of capturing shape variation, our results highlight that techniques based on surface registration provide a reliable methodological framework for working on global shapes without focusing on specific points. We reported in particular that these methods allow the development of tools which are particularly suitable for the paleoanthropological studies.

La modélisation géométrique et la sémantisation de scènes intérieures à partir d'échantillon de points et un sujet de recherche qui prend de plus en plus d'importance. Cependant, le traitement d'un ensemble volumineux de données est rendu difficile d'une part par le nombre élevé d'objets parasitant la scène et d'autre part par divers défauts d'acquisitions comme par exemple des données manquantes ou un échantillonnage de la scène non isotrope. Cette thèse s'intéresse de près à de nouvelles méthodes permettant de modéliser géométriquement un nuage de point non structuré et d’y donner de la sémantique. Dans le chapitre 2, nous présentons deux méthodes permettant de transformer le nuage de points en un ensemble de formes. Nous proposons en premier lieu une méthode d'extraction de lignes qui détecte des segments à partir d'une coupe horizontale du nuage de point initiale. Puis nous introduisons une méthode par croissance de régions qui détecte et renforce progressivement des régularités parmi les formes planaires. Dans la première partie du chapitre 3, nous proposons une méthode basée sur de l'analyse statistique afin de séparer de la structure de la scène les objets la parasitant. Dans la seconde partie, nous présentons une méthode d'apprentissage supervisé permettant de classifier des objets en fonction d'un ensemble de formes planaires. Nous introduisons dans le chapitre 4 une méthode permettant de modéliser géométriquement le volume d'une pièce (sans meubles). Une formulation énergétique est utilisée afin de labelliser les régions d’une partition générée à partir de formes élémentaires comme étant intérieur ou extérieur de manière robuste au bruit et aux données. / Geometric modeling and semantization of indoor scenes from sampled point data is an emerging research topic. Recent advances in acquisition technologies provide highly accurate laser scanners and low-cost handheld RGB-D cameras for real-time acquisition. However, the processing of large data sets is hampered by high amounts of clutter and various defects such as missing data, outliers and anisotropic sampling. This thesis investigates three novel methods for efficient geometric modeling and semantization from unstructured point data: Shape detection, classification and geometric modeling. Chapter 2 introduces two methods for abstracting the input point data with primitive shapes. First, we propose a line extraction method to detect wall segments from a horizontal cross-section of the input point cloud. Second, we introduce a region growing method that progressively detects and reinforces regularities of planar shapes. This method utilizes regularities common to man-made architecture, i.e. coplanarity, parallelism and orthogonality, to reduce complexity and improve data fitting in defect-laden data. Chapter 3 introduces a method based on statistical analysis for separating clutter from structure. We also contribute a supervised machine learning method for object classification based on sets of planar shapes. Chapter 4 introduces a method for 3D geometric modeling of indoor scenes. We first partition the space using primitive shapes detected from permanent structures. An energy formulation is then used to solve an inside/outside labeling of a space partitioning, the latter providing robustness to missing data and outliers.

Doctor of Philosophy / Agronomy / Kevin Price / Stephen M. Welch / Plant phenotyping has been studied for decades for understanding the relationship between plant genotype, phenotype, and the surrounding environment. Improved accuracy and efficiency in plant phenotyping is a critical factor in expediting plant breeding and the selection process. In the past, plant phenotypic traits were extracted using invasive and destructive sampling methods and manual measurements, which were time-consuming, labor-intensive, and cost-inefficient. More importantly, the accuracy and consistency of manual methods can be highly variable. In recent years, however, photogrammetry and 3D modeling techniques have been introduced to extract plant phenotypic traits, but no cost-efficient methods using these two techniques have yet been developed for large-scale plant phenotyping studies. High-throughput 3D modeling techniques in plant biology and agriculture are still in the developmental stages, but it is believed that the temporal and spatial resolutions of these systems are well matched to many plant phenotyping needs. Such technology can be used to help rapid phenotypic trait extraction aid crop genotype selection, leading to improvements in crop yield. In this study, we introduce an automated high-throughput phenotyping pipeline using affordable imaging systems, image processing, and 3D reconstruction algorithms to build 2D mosaicked orthophotos and 3D plant models. Chamber-based and ground-level field implementations can be used to measure phenotypic traits such as leaf length, rosette area in 2D and 3D, plant nastic movement, and diurnal cycles. Our automated pipeline has cross-platform capabilities and a degree of instrument independence, making it suitable for various situations.