The causes of errors in the angle of impact calculation were investigated including the surface type, falling velocity and the method used to fit an ellipse to a bloodstain. As had been cited previously the angle of impact was generally underestimated, especially at acute angles and the reason for this was determined to be due to an overestimation of the length of a bloodstain. The surface type was found to significantly affect the accuracy of an angle of impact calculation and as the falling velocity increased, the angle of impact calculation became more accurate. High-speed photography was used to further investigate the formation of bloodstains on surfaces. It was found that the formation of the bloodstain varied depending on the surface type and the angle of the surface. Bloodstain pattern analysis involves the application of scientific techniques to reconstruct events that resulted in a bloodstain pattern. The position of the blood source in three-dimensional space is a fundamental element of this application. Currently little is known about the methods used by bloodstain pattern analysts to select bloodstains when determining the region of origin. Fourteen analysts worldwide were surveyed in order to ascertain this information. It was found that the methods used were variable and were often not based on scientific research. Research was therefore undertaken into bloodstain selection and in particular, which bloodstains should be selected for a region of origin analysis. As a result of these experiments, two sets of selection criteria were established, one for use when the region of origin is being calculated manually and one for when directional analysis is being used.

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.

O panorama das ciências forenses no Brasil poderia ser mais auspicioso. O aumento incontrolável das dissensões sociais e da criminalidade comum, o crescimento de facções do crime organizado, o surgimento de novas modalidades de delitos, os desastres de massa e o incremento de novas tecnologias são fatores que apontam no sentido de uma maior demanda por exames periciais e da crescente complexidade dos trabalhos relacionados com as ciências forenses. Paradoxalmente, a falta de investimentos públicos na área, os baixos salários, a ausência de perspectiva profissional e o acúmulo de serviço são alguns dos fatores que claramente influenciam na queda de qualidade do trabalho técnico. Não se publicam mais obras de Criminalística e Medicina Legal no país. As revistas especializadas são poucas e os cursos de Direito paulatinamente vão destinando cada vez menos espaço para aquelas que, ao lado da formação jurídica específica, deveriam ser as matérias principais na formação do bacharel, especialmente daqueles que militam na área penal. Além disso, e exatamente pela natureza técnica da matéria, poucos são os questionamentos que recaem sobre a cadeia de custódia ou sobre a validade das provas periciais apresentadas pelos organismos públicos encarregados da prevenção e da repressão criminal. Este trabalho pretende apresentar uma breve revisão dos dispositivos que regulamentam a prova pericial no sistema processual penal, recentemente alterados pela Lei n. 11.690, de 09/06/08, a estrutura da polícia científica e os procedimentos periciais de levantamento dos locais de interesse à Justiça Criminal, desde o momento que antecede à perícia até a entrega do relatório técnico, apontando seus limites, deficiências e qualidades. / The overview of forensic sciences in Brazil could be more auspicious. The uncontrollable raise of social disagreements and common criminality, the increase of organized crime factions, the appearance of new forms of crime, mass disasters and improvement of new technologies are factors which leads to a sense of higher demand for expert examinations and an increasing complexity of works related to forensic sciences. Paradoxically, the absence of public investment in the area, the low wages, the lack of professional perspectives and the accrual of workload are some of the factors that clearly influence the decline of quality of technical works. There are few new publications about Criminalistics and Legal Medicine in Brazil. The specialized journals are few and law schools are gradually giving less space for those which, like specific legal matters, should be the main ones in the training of new lawyers, especially those who work with criminal law. Besides that, and exactly because of the technical nature of the matter, few are the questions which fall upon the chain of custody or the validity of the expert evidence shown by the public organisms which are responsible for the criminal prevention and repression. This dissertation intends to present a brief review of the articles that regulate the expert evidence in the criminal procedural law, recently altered by Law nº 11.690 of 09/06/08, and the structure of forensic science and the expert procedures to gather places of interest to the Criminal Justice, from the moment preceding the expertise until the delivery of the technical report, pointing out its limitations, shortcomings and qualities.

Nous nous intéressons dans cette thèse à la modélisation des interactions entre personnes, objets et scènes. Nous montrons l’intérêt de combiner ces trois sources d’information pour améliorer la classification d’action et la compréhension automatique des scènes. Dans la première partie, nous cherchons à exploiter le contexte fourni par les objets et la scène pour améliorer la classification des actions humaines dans les photographies. Nous explorons différentes variantes du modèle dit de “bag-of-features” et proposons une méthode tirant avantage du contexte scénique. Nous proposons ensuite un nouveau modèle exploitant les objets pour la classification d’action basé sur des paires de détecteurs de parties du corps et/ou d’objet. Nous évaluons ces méthodes sur notre base de données d’images nouvellement collectée ainsi que sur trois autres jeux de données pour la classification d’action et obtenons des résultats proches de l’état de l’art. Dans la seconde partie de cette thèse, nous nous attaquons au problème inverse et cherchons à utiliser l’information contextuelle fournie par les personnes pour aider à la localisation des objets et à la compréhension des scènes. Nous collectons une nouvelle base de données de time-lapses comportant de nombreuses interactions entre personnes, objets et scènes. Nous développons une approche permettant de décrire une zone de l’image par la distribution des poses des personnes qui interagissent avec et nous utilisons cette représentation pour améliorer la localisation d’objets. De plus, nous démontrons qu’utiliser des informations provenant des personnes détectées peut améliorer plusieurs étapes de l’algorithme utilisé pour la compréhension des scènes d’intérieur. Pour finir, nous proposons des annotations 3D de notre base de time-lapses et montrons comment estimer l’espace utilisé par différentes classes d’objets dans une pièce. Pour résumer, les contributions de cette thèse sont les suivantes : (i) nous mettons au point des modèles pour la classification d’image tirant avantage du contexte scénique et des objets environnants et nous proposons une nouvelle base de données pour évaluer leurs performances, (ii) nous développons un nouveau modèle pour améliorer la localisation d’objet grâce à l’observation des acteurs humains interagissant avec une scène et nous le testons sur un nouveau jeu de vidéos comportant de nombreuses interactions entre personnes, objets et scènes, (iii) nous proposons la première méthode pour évaluer les volumes occupés par différentes classes d’objets dans une pièce, ce qui nous permet d’analyser les différentes étapes pour la compréhension automatique de scène d’intérieur et d’en identifier les principales sources d’erreurs. / In this thesis, we focus on modeling interactions between people, objects and scenes and show benefits of combining corresponding cues for improving both action classification and scene understanding. In the first part, we seek to exploit the scene and object context to improve action classification in still images. We explore alternative bag-of-features models and propose a method that takes advantage of the scene context. We then propose a new model exploiting the object context for action classification based on pairs of body part and object detectors. We evaluate our methods on our newly collected still image dataset as well as three other datasets for action classification and show performance close to the state of the art. In the second part of this thesis, we address the reverse problem and aim at using the contextual information provided by people to help object localization and scene understanding. We collect a new dataset of time-lapse videos involving people interacting with indoor scenes. We develop an approach to describe image regions by the distribution of human co-located poses and use this pose-based representation to improve object localization. We further demonstrate that people cues can improve several steps of existing pipelines for indoor scene understanding. Finally, we extend the annotation of our time-lapse dataset to 3D and show how to infer object labels for occupied 3D volumes of a scene. To summarize, the contributions of this thesis are the following: (i) we design action classification models for still images that take advantage of the scene and object context and we gather a new dataset to evaluate their performance, (ii) we develop a new model to improve object localization thanks to observations of people interacting with an indoor scene and test it on a new dataset centered on person, object and scene interactions, (iii) we propose the first method to evaluate the volumes occupied by different object classes in a room that allow us to analyze the current 3D scene understanding pipeline and identify its main source of errors.

This diploma thesis is focused on determine the characteristics of accuracy of the terrestrial laser scanner FARO Focus 3D S120. It is validated the recommended distance between the objects (targets and spheres) and the terrestrial scanner. Next it is tested accuracy of the Cartesian coordinates X, Y, Z measured by laser scanning with resolution 1/2. At the end it is investigated the accuracy of the area determination in X coordinate gained by the scanning of a smooth slightly curved surface.

The aim of this thesis is to scan the part of the interior and exterior of the Faculty of Electrical Engineering and Communication building using the FARO Focus3D X 130 scanner, and the creation of a 3D model in the WGS 84 system. Subsequently, methods, status and utilization research of this technology and point cloud processing software is provided. The collected data are processed in the SCENE. Three-dimensional model is designed using the Pointfuse and Microstation V8i programs. In the end, the registration accuracy of the scans and the resulting 3D model accuracy are evaluated.

This thesis describes problems 3D computer graphic modeling and design graphic system for use in medicine. Design graphic system was successfully implement for concrete application in stomatology.

This dissertation focuses on the many issues that arise from the visual rendering problem. Of primary consideration is light transport simulation, which is known to be computationally expensive. Monte Carlo methods represent a simple and general class of algorithms often used for light transport computation. Unfortunately, the images resulting from Monte Carlo approaches generally suffer from visually unacceptable noise artifacts. The result of any light transport simulation is, by its very nature, an image of high dynamic range (HDR). This leads to the issues of the display of such images on conventional low dynamic range devices and the development of data compression algorithms to store and recover the corresponding large amounts of detail found in HDR images. This dissertation presents our contributions relevant to these issues. Our contributions to high dynamic range image processing include tone mapping and data compression algorithms. This research proposes and shows the efficacy of a novel level set based tone mapping method that preserves visual details in the display of high dynamic range images on low dynamic range display devices. The level set method is used to extract the high frequency information from HDR images. The details are then added to the range compressed low frequency information to reconstruct a visually accurate low dynamic range version of the image. Additional challenges associated with high dynamic range images include the requirements to reduce excessively large amounts of storage and transmission time. To alleviate these problems, this research presents two methods for efficient high dynamic range image data compression. One is based on the classical JPEG compression. It first converts the raw image into RGBE representation, and then sends the color base and common exponent to classical discrete cosine transform based compression and lossless compression, respectively. The other is based on the wavelet transformation. It first transforms the raw image data into the logarithmic domain, then quantizes the logarithmic data into the integer domain, and finally applies the wavelet based JPEG2000 encoder for entropy compression and bit stream truncation to meet the desired bit rate requirement. We believe that these and similar such contributions will make a wide application of high dynamic range images possible. The contributions to light transport simulation include Monte Carlo noise reduction, dynamic object rendering and complex scene rendering. Monte Carlo noise is an inescapable artifact in synthetic images rendered using stochastic algorithm. This dissertation proposes two noise reduction algorithms to obtain high quality synthetic images. The first one models the distribution of noise in the wavelet domain using a Laplacian function, and then suppresses the noise using a Bayesian method. The other extends the bilateral filtering method to reduce all types of Monte Carlo noise in a unified way. All our methods reduce Monte Carlo noise effectively. Rendering of dynamic objects adds more dimension to the expensive light transport simulation issue. This dissertation presents a pre-computation based method. It pre-computes the surface radiance for each basis lighting and animation key frame, and then renders the objects by synthesizing the pre-computed data in real-time. Realistic rendering of complex scenes is computationally expensive. This research proposes a novel 3D space subdivision method, which leads to a new rendering framework. The light is first distributed to each local region to form local light fields, which are then used to illuminate the local scenes. The method allows us to render complex scenes at interactive frame rates. Rendering has important applications in mixed reality. Consistent lighting and shadows between real scenes and virtual scenes are important features of visual integration. The dissertation proposes to render the virtual objects by irradiance rendering using live captured environmental lighting. This research also introduces a virtual shadow generation method that computes shadows cast by virtual objects to the real background. We finally conclude the dissertation by discussing a number of future directions for rendering research, and presenting our proposed approaches.

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With a large population of people who suffer from aphasia, it is imperative that an effective form of therapy is utilized. The purpose of this study was to investigate the effectiveness of augmentative and alternative communication (AAC) programs in improving the communication needs and lives of people affected by aphasia. Individuals (n = 20) suffering from aphasia for 3 months or more completed therapy sessions with speech and language pathologists and the AAC program. Pre- and post-intervention evaluations were administered, consisting of communication satisfaction and success questionnaires, the Western Aphasia Battery (WAB), and probing tests (prompt and response) with an EEG component. Only preliminary data analyses were completed, on three individuals, due to setbacks. All individuals improved on their post-WAB score and average scores on the questionnaires generally increased, but none were statistically significant. However, clinicians noted a clinical significance in improvements, which suggests that AACs are beneficial in aiding and improving people’s communicative functions and daily life. Resting state EEG data of one subject exhibited high mean power spectral densities (PSD) for delta and theta bands in the lobes before and after therapy, supporting previous literature. Mean PSDs of the left frontal lobe demonstrated a statistically significant decrease from pre- to post-, which in the case of the delta and theta bands may indicate possible recovery. More research is necessary to substantiate these conclusions and to explore the use of EEG in mapping brain lesions and tracking the brain’s rehabilitation, as well as the benefits of AACs.