Variable Resolution & Dimensional Mapping For 3d Model Optimization

Three-dimensional computer models, especially geospatial architectural data sets, can be visualized in the same way humans experience the world, providing a realistic, interactive experience. Scene familiarization, architectural analysis, scientific visualization, and many other applications would benefit from finely detailed, high resolution, 3D models. Automated methods to construct these 3D models traditionally has produced data sets that are often low fidelity or inaccurate; otherwise, they are initially highly detailed, but are very labor and time intensive to construct. Such data sets are often not practical for common real-time usage and are not easily updated. This thesis proposes Variable Resolution & Dimensional Mapping (VRDM), a methodology that has been developed to address some of the limitations of existing approaches to model construction from images. Key components of VRDM are texture palettes, which enable variable and ultra-high resolution images to be easily composited; texture features, which allow image features to integrated as image or geometry, and have the ability to modify the geometric model structure to add detail. These components support a primary VRDM objective of facilitating model refinement with additional data. This can be done until the desired fidelity is achieved as practical limits of infinite detail are approached. Texture Levels, the third component, enable real-time interaction with a very detailed model, along with the flexibility of having alternate pixel data for a given area of the model and this is achieved through extra dimensions. Together these techniques have been used to construct models that can contain GBs of imagery data

Ridge Regression Approach to Color Constancy

This thesis presents the work on color constancy and its application in the field of computer vision. Color constancy is a phenomena of representing (visualizing) the reflectance properties of the scene independent of the illumination spectrum. The motivation behind this work is two folds:The primary motivation is to seek ‘consistency and stability’ in color reproduction and algorithm performance respectively because color is used as one of the important features in many computer vision applications; therefore consistency of the color features is essential for high application success. Second motivation is to reduce ‘computational complexity’ without sacrificing the primary motivation.This work presents machine learning approach to color constancy. An empirical model is developed from the training data. Neural network and support vector machine are two prominent nonlinear learning theories. The work on support vector machine based color constancy shows its superior performance over neural networks based color constancy in terms of stability. But support vector machine is time consuming method. Alternative approach to support vectormachine, is a simple, fast and analytically solvable linear modeling technique known as ‘Ridge regression’. It learns the dependency between the surface reflectance and illumination from a presented training sample of data. Ridge regression provides answer to the two fold motivation behind this work, i.e., stable and computationally simple approach. The proposed algorithms, ‘Support vector machine’ and ‘Ridge regression’ involves three step processes: First, an input matrix constructed from the preprocessed training data set is trained toobtain a trained model. Second, test images are presented to the trained model to obtain the chromaticity estimate of the illuminants present in the testing images. Finally, linear diagonal transformation is performed to obtain the color corrected image. The results show the effectiveness of the proposed algorithms on both calibrated and uncalibrated data set in comparison to the methods discussed in literature review. Finally, thesis concludes with a complete discussion and summary on comparison between the proposed approaches and other algorithms

The design and implementation of vision-based behavioural modules for a robotic assembly system

The work drsrrihrd in this thesis ia about, how to program robots to work re liably in the presence of uncertainty. Some architectural principle!: are proposed which address the problem of decomposing robotic assembly tasks into modular units such that a robot program can be implemented efficiently, tested easily, and can be maintained or modified without undue complexity. This architecture also provides a framework to integrate sensors into a robotic, assembly system.These modular units arc called behavioural modules. They perforin their tasks reliably. The problem of uncertainty is dealt with by encapsulating sensing and variation reducing strategies inside these modules. Experiments are performed with a working robotic assembly system using vision based behavioural modules. Analy sis of this system validates the principles presented in this thesis

Vision-Based Building Seismic Displacement Measurement by Stratification of Projective Rectification Using Lines

We propose a new flexible technique for accurate vision-based seismic displacement measurement of building structures via a single non-stationary camera with any perspective view. No a priori information about the camera’s parameters or only partial knowledge of the internal camera parameters is required, and geometric constraints in the world coordinate system are employed for projective rectification in this research. Whereas most projective rectifications are conducted by specifying the positions of four or more fixed reference points, our method adopts a stratified approach to partially determine the projective transformation from line-based geometric relationships on the world plane. Since line features are natural and plentiful in a man-made architectural building environment, robust estimation techniques for automatic projective/affine distortion removal can be applied in a more practical way. Both simulations and real-recorded data were used to verify the effectiveness and robustness of the proposed method. We hope that the proposed method could advance the consumer-grade camera system for vision-based structural measurement one more step, from laboratory environments to real-world structural health monitoring systems

Structure from motion (SFM) photogrammetry

Topographic data measurement is a fundamental aspect of many geomorphic research applications, particularly those including landform monitoring and investigation of changes in topography. However, most surveying techniques require relatively expensive technologies or specialized user supervision. Structure from Motion (SfM) photogrammetric technology lightens both these constraints by allowing the use of consumer grade digital cameras and highly automated data processing, which can be free to use. SfM photogrammetry therefore offers the possibility of fast, automated and low-cost acquisition of 3-D data, which has inevitably created great interest amongst the geomorphological community. In this contribution, the basic concepts of SfM photogrammetry are presented, whilst recognising its heritage. A few examples are employed to illustrate the potential of SfM applications for geomorphological research. In particular, SfM photogrammetry offers to geomorphologists a tool for high-resolution characterisation of 3-D forms at a range of scales and for change detection purposes. The high level of automation of SfM data processing creates both opportunities and threats, particularly because user control tends to focus upon the final product visually rather than upon inherent data quality. Accordingly, this contribution seeks to guide potential new users in successfully applying SfM for a range of geomorphic studies

3D Digital Surveying and Modelling of Cave Geometry: Application to Paleolithic Rock Art

3D digital surveying and modelling of cave geometry represents a relevant approach for research, management and preservation of our cultural and geological legacy. In this paper, a multi-sensor approach based on a terrestrial laser scanner, a high-resolution digital camera and a total station is presented. Two emblematic caves of Paleolithic human occupation and situated in northern Spain, “Las Caldas” and “Peña de Candamo”, have been chosen to put in practise this approach. As a result, an integral and multi-scalable 3D model is generated which may allow other scientists, pre-historians, geologists…, to work on two different levels, integrating different Paleolithic Art datasets: (1) a basic level based on the accurate and metric support provided by the laser scanner; and (2) a advanced level using the range and image-based modelling

3D object reconstruction using computer vision : reconstruction and characterization applications for external human anatomical structures

Tese de doutoramento. Engenharia Informática. Faculdade de Engenharia. Universidade do Porto. 201

From U.A.V. photogrammetry to 3D modeling of the Valencian Silo-Yard in Burjassot

[EN] The importance of recording and documenting cultural and archaeological heritage has provided the opportunity to integrate new technologies and other fields of science for their purpose. The incorporation of geomatics tools allows to generate precision and a wide level of detail in the capture and processing of information. The use of Unmanned Aerial Vehicles (U.A.V.) in order to capture of images around opened spaces with photogrammetric processes permit obtain high quality information. After the process and right use of some software, 3d model can be generated. This project seeks to apply this methodology in an area of archaeological importance located in the City of Valencia (Spain) called as Valencian Silo-Yard. This process has been carried out through different stages where the application and the use of technologies and photogrammetric methodologies applied to the heritage documentation are initially introduced. Further on historical approach has been made to the area under study in order to understand its historical importance and its legacy to the Valencian community. Subsequently the detailed way of the process of acquiring the information and the post-processing performed is described. Finally, this project pursues to apply the methodology in the construction of a 3D model that allows to visualize graphically the detail of the construction and conservation of the area.[ES] La importancia de registrar y documentar el patrimonio arqueológico y cultural ha brindado la oportunidad de integrar nuevas tecnologías y otros campos de la ciencia para su propósito. La incorporación de las herramientas de la Geomática permite generar precisión y un amplio nivel de detalle en la captura y procesamiento de la información. El uso de Vehículos Aéreos no tripulados (U.A.V) con el fin de capturar de imágenes en espacios abiertos con procesos fotogramétricos que permiten obtener una información de alta calidad. Después del proceso y un uso correcto del Software, es posible generar un Modelo 3D. Este proyecto busca aplicar esta metodología en un área de importancia arqueológica está ubicado en la Ciudad de Valencia (España) conocido como La Plaza de los Silos de Valencia. Este proceso se ha llevado a cabo a través de diferentes etapas, donde la aplicación y el uso de tecnologías y la aplicación de metodologías fotogramétricas para la documentación del patrimonio son introducidas desde su inicio. De igual manera, se ha realizado una aproximación histórica en el área objeto de estudio, con el fin de entender su importancia histórica y su legado a la Comunidad Valenciana. Adicionalmente se ha descrito de manera detallada el proceso de adquisición de la información y el post proceso realizado. Finalmente, este Proyecto busca aplicar la metodología en la generación de un modelo 3D que permita observar gráficamente el detalle de la construcción y la conservación del área.Yepes Moya, AP. (2017). From U.A.V. photogrammetry to 3D modeling of the Valencian Silo-Yard in Burjassot. http://hdl.handle.net/10251/139456TFG

Sensor planning for novel view generation by camera networks

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2006.Includes bibliographical references (p. 75-78).This document describes a system for generating novel views of an indoor visual scene by gathering successive 2D images from a set of independent networked robotic cameras. Specifically, the robotic cameras work to seek out texture and geometric information needed to generate the specified synthetic view or views, aiming to-with each successive camera move-increase confidence in the estimates of the pixel intensities in the novel view(s). This system lays the groundwork for future explorations in multi-camera video recording for electroholography and image-based rendering.by James Barabas.S.M