953 resultados para 3D information


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This paper proposes a novel design of a reconfigurable humanoid robot head, based on biological likeness of human being so that the humanoid robot could agreeably interact with people in various everyday tasks. The proposed humanoid head has a modular and adaptive structural design and is equipped with three main components: frame, neck motion system and omnidirectional stereovision system modules. The omnidirectional stereovision system module being the last module, a motivating contribution with regard to other computer vision systems implemented in former humanoids, it opens new research possibilities for achieving human-like behaviour. A proposal for a real-time catadioptric stereovision system is presented, including stereo geometry for rectifying the system configuration and depth estimation. The methodology for an initial approach for visual servoing tasks is divided into two phases, first related to the robust detection of moving objects, their depth estimation and position calculation, and second the development of attention-based control strategies. Perception capabilities provided allow the extraction of 3D information from a wide range of visions from uncontrolled dynamic environments, and work results are illustrated through a number of experiments.

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Tradicionalmente, la fabricación de materiales compuestos de altas prestaciones se lleva a cabo en autoclave mediante la consolidación de preimpregnados a través de la aplicación simultánea de altas presiones y temperatura. Las elevadas presiones empleadas en autoclave reducen la porosidad de los componentes garantizando unas buenas propiedades mecánicas. Sin embargo, este sistema de fabricación conlleva tiempos de producción largos y grandes inversiones en equipamiento lo que restringe su aplicación a otros sectores alejados del sector aeronáutico. Este hecho ha generado una creciente demanda de sistemas de fabricación alternativos al autoclave. Aunque estos sistemas son capaces de reducir los tiempos de producción y el gasto energético, por lo general, dan lugar a materiales con menores prestaciones mecánicas debido a que se reduce la compactación del material al aplicar presiones mas bajas y, por tanto, la fracción volumétrica de fibras, y disminuye el control de la porosidad durante el proceso. Los modelos numéricos existentes permiten conocer los fundamentos de los mecanismos de crecimiento de poros durante la fabricación de materiales compuestos de matriz polimérica mediante autoclave. Dichos modelos analizan el comportamiento de pequeños poros esféricos embebidos en una resina viscosa. Su validez no ha sido probada, sin embargo, para la morfología típica observada en materiales compuestos fabricados fuera de autoclave, consistente en poros cilíndricos y alargados embebidos en resina y rodeados de fibras continuas. Por otro lado, aunque existe una clara evidencia experimental del efecto pernicioso de la porosidad en las prestaciones mecánicas de los materiales compuestos, no existe información detallada sobre la influencia de las condiciones de procesado en la forma, fracción volumétrica y distribución espacial de los poros en los materiales compuestos. Las técnicas de análisis convencionales para la caracterización microestructural de los materiales compuestos proporcionan información en dos dimensiones (2D) (microscopía óptica y electrónica, radiografía de rayos X, ultrasonidos, emisión acústica) y sólo algunas son adecuadas para el análisis de la porosidad. En esta tesis, se ha analizado el efecto de ciclo de curado en el desarrollo de los poros durante la consolidación de preimpregnados Hexply AS4/8552 a bajas presiones mediante moldeo por compresión, en paneles unidireccionales y multiaxiales utilizando tres ciclos de curado diferentes. Dichos ciclos fueron cuidadosamente diseñados de acuerdo a la caracterización térmica y reológica de los preimpregnados. La fracción volumétrica de poros, su forma y distribución espacial se analizaron en detalle mediante tomografía de rayos X. Esta técnica no destructiva ha demostrado su capacidad para analizar la microestructura de materiales compuestos. Se observó, que la porosidad depende en gran medida de la evolución de la viscosidad dinámica a lo largo del ciclo y que la mayoría de la porosidad inicial procedía del aire atrapado durante el apilamiento de las láminas de preimpregnado. En el caso de los laminados multiaxiales, la porosidad también se vio afectada por la secuencia de apilamiento. En general, los poros tenían forma cilíndrica y se estaban orientados en la dirección de las fibras. Además, la proyección de la población de poros a lo largo de la dirección de la fibra reveló la existencia de una estructura celular de un diámetro aproximado de 1 mm. Las paredes de las celdas correspondían con regiones con mayor densidad de fibra mientras que los poros se concentraban en el interior de las celdas. Esta distribución de la porosidad es el resultado de una consolidación no homogenea. Toda esta información es crítica a la hora de optimizar las condiciones de procesado y proporcionar datos de partida para desarrollar herramientas de simulación de los procesos de fabricación de materiales compuestos fuera de autoclave. Adicionalmente, se determinaron ciertas propiedades mecánicas dependientes de la matriz termoestable con objeto de establecer la relación entre condiciones de procesado y las prestaciones mecánicas. En el caso de los laminados unidireccionales, la resistencia interlaminar depende de la porosidad para fracciones volumétricas de poros superiores 1%. Las mismas tendencias se observaron en el caso de GIIc mientras GIc no se vio afectada por la porosidad. En el caso de los laminados multiaxiales se evaluó la influencia de la porosidad en la resistencia a compresión, la resistencia a impacto a baja velocidad y la resistencia a copresión después de impacto. La resistencia a compresión se redujo con el contenido en poros, pero éste no influyó significativamente en la resistencia a compresión despues de impacto ya que quedó enmascarada por otros factores como la secuencia de apilamiento o la magnitud del daño generado tras el impacto. Finalmente, el efecto de las condiciones de fabricación en el proceso de compactación mediante moldeo por compresión en laminados unidireccionales fue simulado mediante el método de los elementos finitos en una primera aproximación para simular la fabricación de materiales compuestos fuera de autoclave. Los parámetros del modelo se obtuvieron mediante experimentos térmicos y reológicos del preimpregnado Hexply AS4/8552. Los resultados obtenidos en la predicción de la reducción de espesor durante el proceso de consolidación concordaron razonablemente con los resultados experimentales. Manufacturing of high performance polymer-matrix composites is normally carried out by means of autoclave using prepreg tapes stacked and consolidated under the simultaneous application of pressure and temperature. High autoclave pressures reduce the porosity in the laminate and ensure excellent mechanical properties. However, this manufacturing route is expensive in terms of capital investment and processing time, hindering its application in many industrial sectors. This fact has driven the demand of alternative out-of-autoclave processing routes. These techniques claim to produce composite parts faster and at lower cost but the mechanical performance is also reduced due to the lower fiber content and to the higher porosity. Corrient numerical models are able to simulate the mechanisms of void growth in polymer-matrix composites processed in autoclave. However these models are restricted to small spherical voids surrounded by a viscous resin. Their validity is not proved for long cylindrical voids in a viscous matrix surrounded by aligned fibers, the standard morphology observed in out-of-autoclave composites. In addition, there is an experimental evidence of the detrimental effect of voids on the mechanical performance of composites but, there is detailed information regarding the influence of curing conditions on the actual volume fraction, shape and spatial distribution of voids within the laminate. The standard techniques of microstructural characterization of composites (optical or electron microscopy, X-ray radiography, ultrasonics) provide information in two dimensions and are not always suitable to determine the porosity or void population. Moreover, they can not provide 3D information. The effect of curing cycle on the development of voids during consolidation of AS4/8552 prepregs at low pressure by compression molding was studied in unidirectional and multiaxial panels. They were manufactured using three different curing cycles carefully designed following the rheological and thermal analysis of the raw prepregs. The void volume fraction, shape and spatial distribution were analyzed in detail by means of X-ray computed microtomography, which has demonstrated its potential for analyzing the microstructural features of composites. It was demonstrated that the final void volume fraction depended on the evolution of the dynamic viscosity throughout the cycle. Most of the initial voids were the result of air entrapment and wrinkles created during lay-up. Differences in the final void volume fraction depended on the processing conditions for unidirectional and multiaxial panels. Voids were rod-like shaped and were oriented parallel to the fibers and concentrated in channels along the fiber orientation. X-ray computer tomography analysis of voids along the fiber direction showed a cellular structure with an approximate cell diameter of 1 mm. The cell walls were fiber-rich regions and porosity was localized at the center of the cells. This porosity distribution within the laminate was the result of inhomogeneous consolidation. This information is critical to optimize processing parameters and to provide inputs for virtual testing and virtual processing tools. In addition, the matrix-controlled mechanical properties of the panels were measured in order to establish the relationship between processing conditions and mechanical performance. The interlaminar shear strength (ILSS) and the interlaminar toughness (GIc and GIIc) were selected to evaluate the effect of porosity on the mechanical performance of unidirectional panels. The ILSS was strongly affected by the porosity when the void contents was higher than 1%. The same trends were observed in the case of GIIc while GIc was insensitive to the void volume fraction. Additionally, the mechanical performance of multiaxial panels in compression, low velocity impact and compression after impact (CAI) was measured to address the effect of processing conditions. The compressive strength decreased with porosity and ply-clustering. However, the porosity did not influence the impact resistance and the coompression after impact strength because the effect of porosity was masked by other factors as the damage due to impact or the laminate lay-up. Finally, the effect of the processing conditions on the compaction behavior of unidirectional AS4/8552 panels manufactured by compression moulding was simulated using the finite element method, as a first approximation to more complex and accurate models for out-of autoclave curing and consolidation of composite laminates. The model parameters were obtained from rheological and thermo-mechanical experiments carried out in raw prepreg samples. The predictions of the thickness change during consolidation were in reasonable agreement with the experimental results.

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The increasing number of works related to the surface texture characterization based on 3D information, makes convenient rethinking traditional methods based on two-dimensional measurements from profiles. This work compares results between measurements obtained using two and three-dimensional methods. It uses three kinds of data sources: reference surfaces, randomly generated surfaces and measured. Preliminary results are presented. These results must be completed trying to cover a wider number of possibilities according to the manufacturing process and the measurement instrumentation since results can vary quite significantly between them.

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In this paper we propose an innovative method for the automatic detection and tracking of road traffic signs using an onboard stereo camera. It involves a combination of monocular and stereo analysis strategies to increase the reliability of the detections such that it can boost the performance of any traffic sign recognition scheme. Firstly, an adaptive color and appearance based detection is applied at single camera level to generate a set of traffic sign hypotheses. In turn, stereo information allows for sparse 3D reconstruction of potential traffic signs through a SURF-based matching strategy. Namely, the plane that best fits the cloud of 3D points traced back from feature matches is estimated using a RANSAC based approach to improve robustness to outliers. Temporal consistency of the 3D information is ensured through a Kalman-based tracking stage. This also allows for the generation of a predicted 3D traffic sign model, which is in turn used to enhance the previously mentioned color-based detector through a feedback loop, thus improving detection accuracy. The proposed solution has been tested with real sequences under several illumination conditions and in both urban areas and highways, achieving very high detection rates in challenging environments, including rapid motion and significant perspective distortion

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El principal objetivo de este trabajo es proporcionar una solución en tiempo real basada en visión estéreo o monocular precisa y robusta para que un vehículo aéreo no tripulado (UAV) sea autónomo en varios tipos de aplicaciones UAV, especialmente en entornos abarrotados sin señal GPS. Este trabajo principalmente consiste en tres temas de investigación de UAV basados en técnicas de visión por computador: (I) visual tracking, proporciona soluciones efectivas para localizar visualmente objetos de interés estáticos o en movimiento durante el tiempo que dura el vuelo del UAV mediante una aproximación adaptativa online y una estrategia de múltiple resolución, de este modo superamos los problemas generados por las diferentes situaciones desafiantes, tales como cambios significativos de aspecto, iluminación del entorno variante, fondo del tracking embarullado, oclusión parcial o total de objetos, variaciones rápidas de posición y vibraciones mecánicas a bordo. La solución ha sido utilizada en aterrizajes autónomos, inspección de plataformas mar adentro o tracking de aviones en pleno vuelo para su detección y evasión; (II) odometría visual: proporciona una solución eficiente al UAV para estimar la posición con 6 grados de libertad (6D) usando únicamente la entrada de una cámara estéreo a bordo del UAV. Un método Semi-Global Blocking Matching (SGBM) eficiente basado en una estrategia grueso-a-fino ha sido implementada para una rápida y profunda estimación del plano. Además, la solución toma provecho eficazmente de la información 2D y 3D para estimar la posición 6D, resolviendo de esta manera la limitación de un punto de referencia fijo en la cámara estéreo. Una robusta aproximación volumétrica de mapping basada en el framework Octomap ha sido utilizada para reconstruir entornos cerrados y al aire libre bastante abarrotados en 3D con memoria y errores correlacionados espacialmente o temporalmente; (III) visual control, ofrece soluciones de control prácticas para la navegación de un UAV usando Fuzzy Logic Controller (FLC) con la estimación visual. Y el framework de Cross-Entropy Optimization (CEO) ha sido usado para optimizar el factor de escala y la función de pertenencia en FLC. Todas las soluciones basadas en visión en este trabajo han sido probadas en test reales. Y los conjuntos de datos de imágenes reales grabados en estos test o disponibles para la comunidad pública han sido utilizados para evaluar el rendimiento de estas soluciones basadas en visión con ground truth. Además, las soluciones de visión presentadas han sido comparadas con algoritmos de visión del estado del arte. Los test reales y los resultados de evaluación muestran que las soluciones basadas en visión proporcionadas han obtenido rendimientos en tiempo real precisos y robustos, o han alcanzado un mejor rendimiento que aquellos algoritmos del estado del arte. La estimación basada en visión ha ganado un rol muy importante en controlar un UAV típico para alcanzar autonomía en aplicaciones UAV. ABSTRACT The main objective of this dissertation is providing real-time accurate robust monocular or stereo vision-based solution for Unmanned Aerial Vehicle (UAV) to achieve the autonomy in various types of UAV applications, especially in GPS-denied dynamic cluttered environments. This dissertation mainly consists of three UAV research topics based on computer vision technique: (I) visual tracking, it supplys effective solutions to visually locate interesting static or moving object over time during UAV flight with on-line adaptivity approach and multiple-resolution strategy, thereby overcoming the problems generated by the different challenging situations, such as significant appearance change, variant surrounding illumination, cluttered tracking background, partial or full object occlusion, rapid pose variation and onboard mechanical vibration. The solutions have been utilized in autonomous landing, offshore floating platform inspection and midair aircraft tracking for sense-and-avoid; (II) visual odometry: it provides the efficient solution for UAV to estimate the 6 Degree-of-freedom (6D) pose using only the input of stereo camera onboard UAV. An efficient Semi-Global Blocking Matching (SGBM) method based on a coarse-to-fine strategy has been implemented for fast depth map estimation. In addition, the solution effectively takes advantage of both 2D and 3D information to estimate the 6D pose, thereby solving the limitation of a fixed small baseline in the stereo camera. A robust volumetric occupancy mapping approach based on the Octomap framework has been utilized to reconstruct indoor and outdoor large-scale cluttered environments in 3D with less temporally or spatially correlated measurement errors and memory; (III) visual control, it offers practical control solutions to navigate UAV using Fuzzy Logic Controller (FLC) with the visual estimation. And the Cross-Entropy Optimization (CEO) framework has been used to optimize the scaling factor and the membership function in FLC. All the vision-based solutions in this dissertation have been tested in real tests. And the real image datasets recorded from these tests or available from public community have been utilized to evaluate the performance of these vision-based solutions with ground truth. Additionally, the presented vision solutions have compared with the state-of-art visual algorithms. Real tests and evaluation results show that the provided vision-based solutions have obtained real-time accurate robust performances, or gained better performance than those state-of-art visual algorithms. The vision-based estimation has played a critically important role for controlling a typical UAV to achieve autonomy in the UAV application.

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Modeling natural phenomena from 3D information enhances our understanding of the environment. Dense 3D point clouds are increasingly used as highly detailed input datasets. In addition to the capturing techniques of point clouds with LiDAR, low-cost sensors have been released in the last few years providing access to new research fields and facilitating 3D data acquisition for a broader range of applications. This letter presents an analysis of different speleothem features using 3D point clouds acquired with the gaming device Microsoft® Kinect. We compare the Kinect sensor with terrestrial LiDAR reference measurements using the KinFu pipeline for capturing complete 3D objects (< 4m**3). The results demonstrate the suitability of the Kinect to capture flowstone walls and to derive morphometric parameters of cave features. Although the chosen capturing strategy (KinFu) reveals a high correlation (R2=0.92) of stalagmite morphometry along the vertical object axis, a systematic overestimation (22% for radii and 44% for volume) is found. The comparison of flowstone wall datasets predominantly shows low differences (mean of 1 mm with 7 mm standard deviation) of the order of the Kinect depth precision. For both objects the major differences occur at strongly varying and curved surface structures (e.g. with fine concave parts).

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The world's largest fossil oyster reef, formed by the giant oyster Crassostrea gryphoides and located in Stetten (north of Vienna, Austria) is studied by Harzhauser et al., 2015, 2016; Djuricic et al., 2016. Digital documentation of the unique geological site is provided by terrestrial laser scanning (TLS) at the millimeter scale. Obtaining meaningful results is not merely a matter of data acquisition with a suitable device; it requires proper planning, data management, and postprocessing. Terrestrial laser scanning technology has a high potential for providing precise 3D mapping that serves as the basis for automatic object detection in different scenarios; however, it faces challenges in the presence of large amounts of data and the irregular geometry of an oyster reef. We provide a detailed description of the techniques and strategy used for data collection and processing in Djuricic et al., 2016. The use of laser scanning provided the ability to measure surface points of 46,840 (estimated) shells. They are up to 60-cm-long oyster specimens, and their surfaces are modeled with a high accuracy of 1 mm. In addition to laser scanning measurements, more than 300 photographs were captured, and an orthophoto mosaic was generated with a ground sampling distance (GSD) of 0.5 mm. This high-resolution 3D information and the photographic texture serve as the basis for ongoing and future geological and paleontological analyses. Moreover, they provide unprecedented documentation for conservation issues at a unique natural heritage site.

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In this thesis, we introduce DeReEs-4v, an algorithm for unsupervised and automatic registration of two video frames captured depth-sensing cameras. DeReEs-4V receives two RGBD video streams from two depth-sensing cameras arbitrary located in an indoor space that share a minimum amount of 25% overlap between their captured scenes. The motivation of this research is to employ multiple depth-sensing cameras to enlarge the field of view and acquire a more complete and accurate 3D information of the environment. A typical way to combine multiple views from different cameras is through manual calibration. However, this process is time-consuming and may require some technical knowledge. Moreover, calibration has to be repeated when the location or position of the cameras change. In this research, we demonstrate how DeReEs-4V registration can be used to find the transformation of the view of one camera with respect to the other at interactive rates. Our algorithm automatically finds the 3D transformation to match the views from two cameras, requires no human interference, and is robust to camera movements while capturing. To validate this approach, a thorough examination of the system performance under different scenarios is presented. The system presented here supports any application that might benefit from the wider field-of-view provided by the combined scene from both cameras, including applications in 3D telepresence, gaming, people tracking, videoconferencing and computer vision.

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Eigen-based techniques and other monolithic approaches to face recognition have long been a cornerstone in the face recognition community due to the high dimensionality of face images. Eigen-face techniques provide minimal reconstruction error and limit high-frequency content while linear discriminant-based techniques (fisher-faces) allow the construction of subspaces which preserve discriminatory information. This paper presents a frequency decomposition approach for improved face recognition performance utilising three well-known techniques: Wavelets; Gabor / Log-Gabor; and the Discrete Cosine Transform. Experimentation illustrates that frequency domain partitioning prior to dimensionality reduction increases the information available for classification and greatly increases face recognition performance for both eigen-face and fisher-face approaches.

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Two sources of uncertainty in the X ray computed tomography imaging of polymer gel dosimeters are investigated in the paper.The first cause is a change in postirradiation density, which is proportional to the computed tomography signal and is associated with a volume change. The second cause of uncertainty is reconstruction noise.A simple technique that increases the residual signal to noise ratio by almost two orders of magnitude is examined.

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We present a new technique called‘Tilt Menu’ for better extending selection capabilities of pen-based interfaces.The Tilt Menu is implemented by using 3D orientation information of pen devices while performing selection tasks.The Tilt Menu has the potential to aid traditional onehanded techniques as it simultaneously generates the secondary input (e.g., a command or parameter selection) while drawing/interacting with a pen tip without having to use the second hand or another device. We conduct two experiments to explore the performance of the Tilt Menu. In the first experiment, we analyze the effect of parameters of the Tilt Menu, such as the menu size and orientation of the item, on its usability. Results of the first experiment suggest some design guidelines for the Tilt Menu. In the second experiment, the Tilt Menu is compared to two types of techniques while performing connect-the-dot tasks using freeform drawing mechanism. Results of the second experiment show that the Tilt Menu perform better in comparison to the Tool Palette, and is as good as the Toolglass.

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[EN]This paper describes a wildfi re forecasting application based on a 3D virtual environment and a fi re simulation engine. A novel open source framework is presented for the development of 3D graphics applications over large geographic areas, off ering high performance 3D visualization and powerful interaction tools for the Geographic Information Systems (GIS) community. The application includes a remote module that allows simultaneous connection of several users for monitoring a real wildfi re event.

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Similarity measure is one of the main factors that affect the accuracy of intensity-based 2D/3D registration of X-ray fluoroscopy to CT images. Information theory has been used to derive similarity measure for image registration leading to the introduction of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. Previous attempt to incorporate spatial information into mutual information either requires computing the entropy of higher dimensional probability distributions, or is not robust to outliers. In this paper, we show how to incorporate spatial information into mutual information without suffering from these problems. Using a variational approximation derived from the Kullback-Leibler bound, spatial information can be effectively incorporated into mutual information via energy minimization. The resulting similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experimental results are presented on datasets of two applications: (a) intra-operative patient pose estimation from a few (e.g. 2) calibrated fluoroscopic images, and (b) post-operative cup alignment estimation from single X-ray radiograph with gonadal shielding.