Multiview Stereo Object Reconstruction with a One-Line Search Method

published_or_final_versio

Structure and motion estimation from apparent contours under circular motion

In this paper, we address the problem of recovering structure and motion from the apparent contours of a smooth surface. Fixed image features under circular motion and their relationships with the intrinsic parameters of the camera are exploited to provide a simple parameterization of the fundamental matrix relating any pair of views in the sequence. Such a parameterization allows a trivial initialization of the motion parameters, which all bear physical meaning. It also greatly reduces the dimension of the search space for the optimization problem, which can now be solved using only two epipolar tangents. In contrast to previous methods, the motion estimation algorithm introduced here can cope with incomplete circular motion and more widely spaced images. Existing techniques for model reconstruction from apparent contours are then reviewed and compared. Experiment on real data has been carried out and the 3D model reconstructed from the estimated motion is presented. © 2002 Elsevier Science B.V. All rights reserved.postprin

How to Decide From the First View Where to Look Next

The task of constructing a volumetric description of a scene from a single image is an underdetermined problem, whether it is a range or an intensity image. To resolve the ambiguities that are caused by occlusions in images, we need to take sensor measurements from several different views. We have limited ourselves to the range images obtained by a laser scanning system. It is an active binocular system which can encounter two types of occlusions. An occlusion arises either when the reflected laser light does not reach the camera or when the directed laser light does not reach the scene surface. The task of 3-D data acquisition is divided into two subproblems: to see what is illuminated and to properly direct the illuminating plane to illuminate the entire scene. The first kind of occlusions are easily detected and can be used in designing an efficient algorithm. We develop a strategy to determine the sequence of different views using the information in a narrow zone around the occluded regions. Occluded regions are approximated by polygons. Based on the height information of the border of the occluded regions and geometry of the edges of the polygonal approximation, the next views in the same scanning plane are determined. From the acquired information in the first scanning plane the directions of the next scanning planes are computed

3D reconstruction of point clouds using multi-view orthographic projections

Cataloged from PDF version of article.A method to reconstruct 3D point clouds using multi-view orthographic projections is examined. Point clouds are generated by means of a stochastic process. This stochastic process is designed to generate point clouds that mimic microcalcification formation in breast tissue. Point clouds are generated using a Gibbs sampler algorithm. Orthographic projections of point clouds from any desired orientation are generated. Volumetric intersection method is employed to perform the reconstruction from these orthographic projections. The reconstruction may yield erroneous reconstructed points. The types of these erroneous points are analyzed along with their causes and a performance measure based on linear combination is devised. Experiments have been designed to investigate the effect of the number of projections and the number of points to the performance of reconstruction. Increasing the number of projections and decreasing the number of points resulted in better reconstructions that are more similar to the original point clouds. However, it is observed that reconstructions do not improve considerably upon increasing the number of projections after some number. This method of reconstruction serves well to find locations of original points.Topçu, OsmanM.S

Occlusions as a Guide for Planning the Next View

To resolve the ambiguities that are caused by occlusions in images, we need to take sensor measurements from several different views. The task addressed in this paper deals with a strategy for acquiring 3-D data of an unknown scene. We must first answer the question: What knowledge is adequate to perform a specific task? Thinking in the spirit of purposive vision, to accomplish its task, a system does not need to understand the complete scene but must be able to recognize patterns and situations that are necessary for accomplishing the task. We have limited ourselves to range images obtained by a light stripe range finder. A priori knowledge given to the system is the knowledge of the sensor geometry. The foci of attention are occluded regions, i.e., only the scene at the borders of the occlusions is modeled to compute the next move. Since the system has knowledge of the sensor geometry, it can resolve the appearance of occlusions by analyzing them. The problem of 3-D data acquisition is divided in two subproblems due to two types of occlusions. An occlusion arises either when the reflected laser light does not reach the camera or when the directed laser light does not reach the scene surface. After taking the range image of a scene the regions of no data due to the first kind of occlusion are extracted. The missing data are acquired by rotating the sensor system in the scanning plane, which is defined by the first scan. After a complete image of the surface illuminated from the first scanning plane has been built, the regions of missing data which are due to the second kind of occlusions are located. Then the directions of the next scanning planes for further 3-D data acquisition are computed

Obtención de mapas 2.5D mediante RTI (Reflectance Transformation Imaging) para su aplicación en el Patrimonio Escultórico, Arqueológico, Arquitectónico y Urbano.

Desde los orígenes, el ser humano ha tratado de encontrar métodos que mejoren o posibiliten alcanzar objetivos que el cuerpo humano es incapaz. Aunque éste es altamente complejo, no es perfecto y el ojo humano es limitado en términos de profundidad (visión estereo) y color. Por ello se crea el método de trabajo conocido como Flujo Clásico para RTI, que posibilita extraer información oculta de objetos con mínima variación de cota. 1. Realidad Objeto 2. Toma de Fotos Domo con Luces en determinadas posiciones y Cámara Cenital 3. Generación PTM RTIBuilder (X, Y, Normal Vector) 4. Visor RTIViewer (SnapShot) Este flujo de trabajo parte de un objeto de tamaño pequeño. Al cual se le aplica, junto a un par de esferas reflectivas, una serie de fotografías mediante una cámara cenital y diferentes posiciones de proyección de luz inscritas en un Domo geométrico para mantener las equidistancias a la superficie de análisis. Tras ello se pasa al trabajo en ordenador donde se genera un archivo de superficies de normales (*.ptm o *.hsh) mediante los algoritmos de Polynomial Texture Mapping o Hemispherical Harmonics en RTIBuilder. El cual puede ser analizado mediante el Visor que presenta el RTIViewer. Este Flujo de Trabajo Clásico no puede afrontar factores como la luz natural, transforma las direcciones de la proyección de la iluminación, o las dimensiones del objeto/edificación/terreno a trabajar. Es por ello que se propone el Nuevo Flujo de Trabajo RTI-DPh, la virtualización del Clásico Flujo de Trabajo RTI.Departamento de Urbanismo y Representación de la ArquitecturaMáster en Geotecnologías Cartográficas en Ingeniería y Arquitectur