Download or read book AN ALGORITHM FOR RECONSTRUCTING THREE DIMENSIONAL IMAGES FROM OVERLAPPING TWO DIMENSIONAL INTENSITY MEASUREMENTS WITH RELAXED CAMERA POSITIONING REQUIREMENTS WITH APPLICATION TO ADDITIVE MANUFACTURING written by and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract : Cameras are everywhere for security purposes and there are often many cameras installed close to each other to cover areas of interest, such as airport passenger terminals. These systems are often designed to have overlapping fields of view to provide different aspects of the scene to review when, for example, law enforcement issues arise. However, these cameras are rarely, if ever positioned in a way that would be conducive to conventional stereo image processing. To address this, issue an algorithm was developed to rectify images measured under such conditions, and then perform stereo image reconstruction. The initial experiments described here were set up using two scientific cameras to capture overlapping images in various cameras positons. The results showed that the algorithm was accurately reconstructing the three-dimensional (3-D) surface locations of the input objects. During the research an opportunity arose to further develop and test the algorithms for the problem of monitoring the fabrication process inside a 3-D printer. The geometry of 3-D printers prevents the location of cameras in the conventional stereo imaging geometry, making the algorithms described above seem like an attractive solution to this problem. The emphasis in 3-D printing on using extremely low cost components and open source software, and the need to develop the means of comparing observed progress in the fabrication process to a model of the device being fabricated posed additional development challenges. Inside the 3-D printer the algorithm was applied using two scientific cameras to detect the errors during the printing of the low-cost open-source RepRap style 3-D printer developed by the Michigan Tech's Open Sustainability Technology Lab. An algorithm to detect errors in the shape of a device being fabricated using only one camera was also developed. The results show that a 3-D reconstruction algorithm can be used to accurately detect the 3-D printing errors. The initial development of the algorithm was in MATLAB. The cost of the MATLAB software might prevent it from being used by open-source communities. Thus, the algorithm was ported to Python and made open-source for everyone to use and customize. To reduce the cost, the commonly used and widely available inexpensive webcams were also used instead of the expensive scientific cameras. In order to detect errors around the printed part, six webcams were used, so there were 3 pairs of webcams and each pair were 120 degrees apart. The results indicated that the algorithms are precisely detect the 3-D printing errors around the printed part in shape and size aspects. With this low-cost and open-source approach, the algorithms are ready for wide range of use and applications.

Download or read book Three dimensional Object Reconstruction Using Structured Light and Two Two dimensional Images written by Philippe Lavoie and published by . This book was released on 1996 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: For machine vision and for graphical representation of real objects in a computer environment, the three-dimensional (3D) reconstruction of the image of a real object has become a key technique. A few methods such as range finding, which use laser scanners, computer tomography, based on CTR or MRI machines, computational stereo, etc. were developed. Computational stereo is broadly defined as the recovery of 3D characteristics of a scene from a series of images obtained from different points in the three dimensional (Euclidean) space. In this thesis, a new algorithm and system is introduced and developed for the 3D reconstruction of the images of real objects from two 2D images required with two cameras. The algorithm is based on a new matching method, a new procedure for the determination of the fundamental matrix used in stereo vision, and a new technique for stereo fusion. The novelty of the matching procedure, and of the determination of the camera alignment, consists of the projection of a structured light pattern on the real object, the pattern being created using a pseudo-random encoded mesh (PRBA) (34). The novelty of the stereo fusion algorithm consists of the application of the dynamic programming principle (DP) (5) (27) using a cost function which contains the information obtained from the list of matched points. It is also proposed to use an autoregressive (AR) modeling technique for calculating the stereo disparity of each pixel of the two images. The autoregressive filter helps the DP part of the algorithm to calculate the disparity of the pixels when the above pixels are occluded. The above proposed methods offer three distinctive advantages over a conventional stereo system: (1) It easily generates a list of matching points. (2) It adds structure to an object without textures. (3) It is less computational intensive.

Download or read book 3D Reconstruction from Multiple Images written by Theo Moons and published by Now Publishers Inc. This book was released on 2009-10-23 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: The issue discusses methods to extract 3-dimensional (3D) models from plain images. In particular, the 3D information is obtained from images for which the camera parameters are unknown. The principles underlying such uncalibrated structure-from-motion methods are outlined. First, a short review of 3D acquisition technologies puts such methods in a wider context, and highlights their important advantages. Then, the actual theory behind this line of research is given. The authors have tried to keep the text maximally self-contained, therefore also avoiding to rely on an extensive knowledge of the projective concepts that usually appear in texts about self-calibration 3D methods. Rather, mathematical explanations that are more amenable to intuition are given. The explanation of the theory includes the stratification of reconstructions obtained from image pairs as well as metric reconstruction on the basis of more than 2 images combined with some additional knowledge about the cameras used. Readers who want to obtain more practical information about how to implement such uncalibrated structure-from-motion pipelines may be interested in two more Foundations and Trends issues written by the same authors. Together with this issue they can be read as a single tutorial on the subject.

Download or read book A Framework for Realtime 3 D Reconstruction by Space Carving Using Graphics Hardware written by Christian Nitschke and published by diplom.de. This book was released on 2007-03-05 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inhaltsangabe:Introduction: Reconstruction of real-world scenes from a set of multiple images is a topic in Computer Vision and 3D Computer Graphics with many interesting applications. There is a relation to Augmented and Mixed Reality (AR/MR), Computer-Supported Collaborative Work (CSCW), Computer-Aided industrial/architectural Design (CAD), modeling of the real-world (e.g. computer games, scenes/effects in movies), entertainment (e.g. 3D TV/Video) and recognition/analyzing of real-world characteristics by computer systems and robots. There exists a powerful algorithm theory for shape reconstruction from arbitrary viewpoints, called shape from photo-consistency. However, it is computationally expensive and hence can not be used with applications in the field of 3D video or CSCW as well as interactive 3D model creation. Attempts have been made to achieve real-time framerates using PC cluster systems. While these provide enough performance they are also expensive and less flexible. Approaches that use GPU hardware-acceleration on single workstations achieve interactive framerates for novel-view synthesis, but do not provide an explicit volumetric representation of the whole scene. The proposed approach shows the efforts in developing a GPU hardware-accelerated framework for obtaining the volumetric photo hull of a dynamic 3D scene as seen from multiple calibrated cameras. High performance is achieved by employing a shape from silhouette technique in advance to obtain a tight initial volume for shape from photo-consistency. Also several speed-up techniques are presented to increase efficiency. Since the entire processing is done on a single PC, the framework can be applied to mobile setups, enabling a wide range of further applications. The approach is explained using programmable vertex and fragment processors and compared to highly optimized CPU implementations. It is shown that the new approach can outperform the latter by more than one magnitude. The thesis is organized as follows: Chapter 1 contains an introduction, giving an overview with classification of related techniques, statement of the main problem, novelty of the proposed approach and its fields of application. Chapter 2 surveys related work in the area of dynamic scene reconstruction by shape from silhouette and shape from photo-consistency. The focus lies on high performance reconstruction and hardware-acceleration. Chapter 3 introduces the theoretical basis for the proposed [...]

Download or read book 3 D Shape Estimation and Image Restoration written by Paolo Favaro and published by Springer Science & Business Media. This book was released on 2007-03-12 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the areas of image processing and computer vision, there is a particular need for software that can, given an unfocused or motion-blurred image, infer the three-dimensional shape of a scene. This book describes the analytical processes that go into designing such software, delineates the options open to programmers, and presents original algorithms. Written for readers with interests in image processing and computer vision and with backgrounds in engineering, science or mathematics, this highly practical text/reference is accessible to advanced students or those with a degree that includes basic linear algebra and calculus courses.

Download or read book A Reconstruction Algorithm for a Three dimensional Positron Camera written by Charles William Stearns and published by . This book was released on 1986 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Iterative Optimizing Quantization Method for Reconstructing Three dimensional Images from a Limited Number of Views written by and published by . This book was released on 1997 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A three-dimensional image reconstruction method comprises treating the object of interest as a group of elements with a size that is determined by the resolution of the projection data, e.g., as determined by the size of each pixel. One of the projections is used as a reference projection. A fictitious object is arbitrarily defined that is constrained by such reference projection. The method modifies the known structure of the fictitious object by comparing and optimizing its four projections to those of the unknown structure of the real object and continues to iterate until the optimization is limited by the residual sum of background noise. The method is composed of several sub-processes that acquire four projections from the real data and the fictitious object: generate an arbitrary distribution to define the fictitious object, optimize the four projections, generate a new distribution for the fictitious object, and enhance the reconstructed image. The sub-process for the acquisition of the four projections from the input real data is simply the function of acquiring the four projections from the data of the transmitted intensity. The transmitted intensity represents the density distribution, that is, the distribution of absorption coefficients through the object.

Download or read book Reconstruction Techniques for Fixed 3 D Lines and Fixed 3 D Points Using the Relative Pose of One Or Two Cameras written by Roshan Satish Kalghatgi and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In general, stereovision can be defined as a two part problem. The first is the correspondence problem. This involves determining the image point in each image of a set of images that correspond to the same physical point P. We will call this set of image points, N. The second problem is the reconstruction problem. Once a set of image points, N, that correspond to point P has been determined, N is then used to extract three dimensional information about point P. This master's thesis presents three novel solutions to the reconstruction problem. Two of the techniques presented are for detecting the location of a 3-D point and one for detecting a line expressed in a three dimensional coordinate system. These techniques are tested and validated using a unique 3-D finger detection algorithm. The techniques presented are unique because of their simplicity and because they do not require the cameras to be placed in specific locations, orientations or have specific alignments. On the contrary, it will be shown that the techniques presented in this thesis allow the two cameras used to assume almost any relative pose provided that the object of interest is within their field of view. The relative pose of the cameras at a given instant in time, along with basic equations from the perspective image model are used to form a system of equations that when solved, reveal the 3-D coordinates of a particular fixed point of interest or the three dimensional equation of a fixed line of interest. Finally, it will be shown that a single moving camera can successfully perform the same line and point detection accomplished by two cameras by altering the pose of the camera. The results presented in this work are beneficial to any typical stereovision application because of the computational ease in comparison to other point and line reconstruction techniques. But more importantly, this work allows for a single moving camera to perceive three-dimensional position information, which effectively removes the two camera constraint for a stereo vision system. When used with other monocular cues such as texture or color, the work presented in this thesis could be as accurate as binocular stereo vision at interpreting three dimensional information. Thus, this work could potentially increase the three dimensional perception of a robot that normally uses one camera, such as an eye-in-hand robot or a snake like robot.

Download or read book View Synthesis Using Stereo Vision written by Daniel Scharstein and published by Springer. This book was released on 2003-06-29 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image-based rendering, as an area of overlap between computer graphics and computer vision, uses computer vision techniques to aid in sythesizing new views of scenes. Image-based rendering methods are having a substantial impact on the field of computer graphics, and also play an important role in the related field of multimedia systems, for applications such as teleconferencing, remote instruction and surgery, virtual reality and entertainment. The book develops a novel way of formalizing the view synthesis problem under the full perspective model, yielding a clean, linear warping equation. It shows new techniques for dealing with visibility issues such as partial occlusion and "holes". Furthermore, the author thoroughly re-evaluates the requirements that view synthesis places on stereo algorithms and introduces two novel stereo algorithms specifically tailored to the application of view synthesis.

Download or read book Reconstruction of Three Dimensional Surfaces from Two Dimensional Binary Images written by D. Raviv and published by . This book was released on 1987 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Reconstructing 3D Geometry from Multiple Images Via Inverse Rendering written by John William Bastian and published by . This book was released on 2007 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: An image is a two-dimensional representation of the three-dimensional world. Recovering the information which is lost in the process of image formation is one of the fundamental problems in Computer Vision. One approach to this problem involves generating and evaluating a succession of surface hypotheses, with the best hypothesis selected as the final estimate. The fitness of each hypothesis can be evaluated by comparing the reference images against synthetic images of the hypothesised surface rendered with the reference cameras.

Download or read book Representations and Techniques for 3D Object Recognition and Scene Interpretation written by Derek Hoiem and published by Morgan & Claypool Publishers. This book was released on 2011 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physical scenes from images. The second section introduces representations for 3D object categories that account for the intrinsically 3D nature of objects and provide robustness to change in viewpoints. The third section discusses strategies to unite inference of scene geometry and object pose and identity into a coherent scene interpretation. Each section broadly surveys important ideas from cognitive science and artificial intelligence research, organizes and discusses key concepts and techniques from recent work in computer vision, and describes a few sample approaches in detail. Newcomers to computer vision will benefit from introductions to basic concepts, such as single-view geometry and image classification, while experts and novices alike may find inspiration from the book's organization and discussion of the most recent ideas in 3D scene understanding and 3D object recognition. Specific topics include: mathematics of perspective geometry; visual elements of the physical scene, structural 3D scene representations; techniques and features for image and region categorization; historical perspective, computational models, and datasets and machine learning techniques for 3D object recognition; inferences of geometrical attributes of objects, such as size and pose; and probabilistic and feature-passing approaches for contextual reasoning about 3D objects and scenes. Table of Contents: Background on 3D Scene Models / Single-view Geometry / Modeling the Physical Scene / Categorizing Images and Regions / Examples of 3D Scene Interpretation / Background on 3D Recognition / Modeling 3D Objects / Recognizing and Understanding 3D Objects / Examples of 2D 1/2 Layout Models / Reasoning about Objects and Scenes / Cascades of Classifiers / Conclusion and Future Directions

Download or read book Image Point Matching in Multiple View Object Reconstruction from Image Sequences written by Jian Zhang and published by . This book was released on 2017-01-26 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "Image Point Matching in Multiple-view Object Reconstruction From Image Sequences" by Jian, Zhang, 张简, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: This thesis is concerned with three-dimensional (3D) reconstruction and point registration, which are fundamental topics of numerous applications in the area of computer vision. First, we propose the multiple epipolar lines (MEL) shape recovery method for 3D reconstruction from an image sequence captured under circular motion. This method involves recovering the 3D shape by reconstructing a set of 3D rim curves. The position of each point on a 3D rim curve is estimated by using three or more views. Two or more of these views are chosen close to each other to guarantee good image point matching, while one or more views are chosen far from these views to properly compensate for the error introduced in the triangulation scheme by the short baseline of the close views. Image point matching among all views is performed using a new method that suitably combines epipolar geometry and cross-correlation. Second, we develop the one line search (OLS) method for estimating the 3D model of an object from a sequence of images. The recovered object comprises a set of 3D rim curves. The OLS method determines the image point correspondences of each 3D point through a single line search along the ray defined by the camera center and each two-dimensional (2D) point where a photo-consistency index is maximized. In accordance with the approach, the search area is independently reduced to a line segment on the number of views. The key advantage of the proposed method is that only one variable is focused on in defining the corresponding 3D point, whereas the approaches for multiple-view stereo typically exploit multiple epipolar lines and hence require multiple variables. Third, we propose the expectation conditional maximization for point registration (ECMPR) algorithm to solve the rigid point registration problem by fitting the problem into the framework of maximum likelihood with missing data. The unknown correspondences are handled via mixture models. We derive a maximization criterion based on the expected complete-data log-likelihood. Then, the point registration problem can be solved by an instance of the expectation conditional maximization algorithm, that is, the ECMPR algorithm. Experiments with synthetic and real data are presented in each section. The proposed approaches provide satisfactory and promising results. DOI: 10.5353/th_b4807985 Subjects: Three-dimensional imaging Image reconstruction Image processing

Download or read book Three dimensional Object Reconstruction from Range Images written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This research work focuses on reconstructing surface models from range images of three-dimensional (3D) objects. This problem of surface reconstruction from range images is very important in the design of any 3D computer vision system and normally consists of several phases of data processing. This work presents novel algorithms to provide efficient solutions used in the following four key phases: data acquisition, data registration from multiple views, data integration, and surface reconstruction. In the phase of data acquisition, two model-based approaches, the area model (AM) and line model (LM), are proposed to model the systematical error of a given ranging system (4DI system), and error lookup table is built with these models and used to reduce the systematical error of acquired data. In the phase of data registration, a registration method involving geometric transformation is presented for reconstructing large object from multiple views with high accuracy. The algorithm provides highly precise numerical values for the elements of the transformation matrices. These values are determined by the specific system parameters estimated through carefully designed tests. In the phase of data integration, a novel data integration approach which is based on predefined criteria and the nearest neighbor searching is developed. Our method manipulates surface points directly, thus, it provides a simple and fast way for overlap removal. In the phase of surface reconstruction, an algorithm for meshing is proposed. It considers the shape change at the boundary of mesh area and forces mesh area to propagate according to a priority driven based strategy. New criteria for triangulation are developed to construct triangle at each step of mesh growing. All these approaches are successfully applied to various range data sets of objects with different geometrical shapes.

Download or read book Three dimensional Image Capture and Applications written by and published by . This book was released on 1998 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book 3D Reconstruction from 2D Camera Perspectives written by Muhammad Abuzar Fahiem and published by LAP Lambert Academic Publishing. This book was released on 2011-04 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: Engineering industry requires line drawings for manufacturing, machining and production of engineering equipments/objects. The generation of these paper-based drawings or computerized drawings is a complex and time consuming task. Conventionally, these drawings contain three two dimensional (2D) orthographic views, namely top, front and side of an object. Modern trends in engineering industry require three dimensional (3D) engineering drawings. Therefore, to fulfill this requirement the conversion of these 2D drawings to 3D drawings is essential. This conversion is referred to as the reconstruction. Various approaches have been proposed for the conversion/reconstruction using existing drawings. In this thesis, we developed 3D reconstruction methodology that uses camera perspectives in the reconstruction process. Note that in the existing approaches this feature (camera perspective) is not used. Another salient feature of our approach is in its underlying mechanism of tangential lines and hypothetical cuboid. Using our proposed approach, manufacturing cost and time can be saved, and it can also be helpful in technology transfer.

Download or read book Guide to Three Dimensional Structure and Motion Factorization written by Guanghui Wang and published by Springer. This book was released on 2012-11-06 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem of structure and motion recovery from image sequences is an important theme in computer vision. Considerable progress has been made in this field during the past two decades, resulting in successful applications in robot navigation, augmented reality, industrial inspection, medical image analysis, and digital entertainment, among other areas. However, many of these methods work only for rigid objects and static scenes. The study of non-rigid structure from motion is not only of academic significance, but also has important practical applications in real-world, nonrigid or dynamic scenarios, such as human facial expressions and moving vehicles. This practical guide/reference provides a comprehensive overview of Euclidean structure and motion recovery, with a specific focus on factorization-based algorithms. The book discusses the latest research in this field, including the extension of the factorization algorithm to recover the structure of non-rigid objects, and presents some new algorithms developed by the authors. Readers require no significant knowledge of computer vision, although some background on projective geometry and matrix computation would be beneficial. Topics and features: presents the first systematic study of structure and motion recovery of both rigid and non-rigid objects from images sequences; discusses in depth the theory, techniques, and applications of rigid and non-rigid factorization methods in three dimensional computer vision; examines numerous factorization algorithms, covering affine, perspective and quasi-perspective projection models; provides appendices describing the mathematical principles behind projective geometry, matrix decomposition, least squares, and nonlinear estimation techniques; includes chapter-ending review questions, and a glossary of terms used in the book. This unique text offers practical guidance in real applications and implementations of 3D modeling systems for practitioners in computer vision and pattern recognition, as well as serving as an invaluable source of new algorithms and methodologies for structure and motion recovery for graduate students and researchers.