Dense real-time 3D reconstruction from multiple images

The rapid increase in computer graphics and acquisition technologies has led to the widespread use of 3D models. Techniques for 3D reconstruction from multiple views aim to recover the structure of a scene and the position and orientation (motion) of the camera using only the geometrical constraints in 2D images. This problem, known as Structure from Motion (SfM) has been the focus of a great deal of research effort in recent years; however, the automatic, dense, real-time and accurate reconstruction of a scene is still a major research challenge. This thesis presents work that targets the development of efficient algorithms to produce high quality and accurate reconstructions, introducing new computer vision techniques for camera motion calibration, dense SfM reconstruction and dense real-time 3D reconstruction. In SfM, a second challenge is to build an effective reconstruction framework that provides dense and high quality surface modelling. This thesis develops a complete, automatic and flexible system with a simple user-interface of `raw images to 3D surface representation'. As part of the proposed image reconstruction approach, this thesis introduces an accurate and reliable region-growing algorithm to propagate the dense matching points from the sparse key points among all stereo pairs. This dense 3D reconstruction proposal addresses the deficiencies of existing SfM systems built on sparsely distributed 3D point clouds which are insufficient for reconstructing a complete 3D model of a scene. The existing SfM reconstruction methods perform a bundle adjustment optimization of the global geometry in order to obtain an accurate model. Such an optimization is very computational expensive and cannot be implemented in a real-time application. Extended Kalman Filter (EKF) Simultaneous Localization and Mapping (SLAM) considers the problem of concurrently estimating in real-time the structure of the surrounding world, perceived by moving sensors (cameras), simultaneously localizing in it. However, standard EKF-SLAM techniques are susceptible to errors introduced during the state prediction and measurement prediction linearization.

Meaning construction in popular science : an investigation into cognitive, digital, and empirical approaches to discourse reification

This thesis uses cognitive linguistics and digital humanities techniques to analyse abstract conceptualization in a corpus of popular science texts. Combining techniques from Conceptual Integration Theory, corpus linguistics, data-mining, cognitive pragmatics and computational linguistics, it presents a unified approach to understanding cross-domain mappings in this area, and through case studies of key extracts, describes how concept integration in these texts operates. In more detail, Part I of the thesis describes and implements a comprehensive procedure for semantically analysing large bodies of text using the recently- completed database of the Historical Thesaurus of English. Using log-likelihood statistical measures and semantic annotation techniques on a 600,000 word corpus of abstract popular science, this part establishes both the existence and the extent of significant analogical content in the corpus. Part II then identifies samples which are particularly high in analogical content from the corpus, and proposes an adaptation of empirical and corpus methods to support and enhance conceptual integration (sometimes called conceptual blending) analyses, informed by Part I’s methodologies for the study of analogy on a wider scale. Finally, the thesis closes with a detailed analysis, using this methodology, of examples taken from the example corpus. This analysis illustrates those conclusions which can be drawn from such work, completing the methodological chain of reasoning from wide-scale corpora to narrow-focus semantics, and providing data about the nature of highly-abstract popular science as a genre. The thesis’ original contribution to knowledge is therefore twofold; while contributing to the understanding of the reification of abstractions in discourse, it also focuses on methodological enhancements to existing tools and approaches, aiming to contribute to the established tradition of both analytic and procedural work advancing the digital humanities in the area of language and discourse

A method for obtaining the tesseract by unraveling the 4D hypercube

This article presents a method for unraveling the hypercube and obtaining the 3D-cross (tesseract) that corresponds to the hyper-flattening of its boundary. The hypercube can be raveled back using the method in an inverse way. Also a method for visualizing the processes is presented. The transformations to apply include rotations around a plane (characteristic of the 4D space). All these processes can be viewed using a computer animation system

A Method For Obtaining The Tesseract By Unraveling The 4D Hypercube

This article presents a method for unraveling the hypercube and obtaining the 3D-cross (tesseract) that corresponds to the hyper-flattening of its boundary. The hypercube can be raveled back using the method in an inverse way. Also a method for visualizing the processes is presented. The transformations to apply include rotations around a plane (characteristic of the 4D space). All these processes can be viewed using a computer animation system. Keywords: 4D-Modeling, 4D-Animation, Computational Geometry. 1