Statistical Approaches to Inferring Object Shape from Single Images

Depth inference is a fundamental problem of computer vision with a broad range of potential applications. Monocular depth inference techniques, particularly shape from shading dates back to as early as the 40's when it was first used to study the shape of the lunar surface. Since then there has been ample research to develop depth inference algorithms using monocular cues. Most of these are based on physical models of image formation and rely on a number of simplifying assumptions that do not hold for real world and natural imagery. Very few make use of the rich statistical information contained in real world images and their 3D information. There have been a few notable exceptions though. The study of statistics of natural scenes has been concentrated on outdoor scenes which are cluttered. Statistics of scenes of single objects has been less studied, but is an essential part of daily human interaction with the environment. Inferring shape of single objects is a very important computer vision problem which has captured the interest of many researchers over the past few decades and has applications in object recognition, robotic grasping, fault detection and Content Based Image Retrieval (CBIR). This thesis focuses on studying the statistical properties of single objects and their range images which can benefit shape inference techniques. I acquired two databases: Single Object Range and HDR (SORH) and the Eton Myers Database of single objects, including laser-acquired depth, binocular stereo, photometric stereo and High Dynamic Range (HDR) photography. I took a data driven approach and studied the statistics of color and range images of real scenes of single objects along with whole 3D objects and uncovered some interesting trends in the data. The fractal structure of natural images was previously well known, and thought to be a universal property. However, my research showed that the fractal structure of single objects and surfaces is governed by a wholly different set of rules. Classical computer vision problems of binocular and multi-view stereo, photometric stereo, shape from shading, structure from motion, and others, all rely on accurate and complete models of which 3D shapes and textures are plausible in nature, to avoid producing unlikely outputs. Bayesian approaches are common for these problems, and hopefully the findings on the statistics of the shape of single objects from this work and others will both inform new and more accurate Bayesian priors on shape, and also enable more efficient probabilistic inference procedures

The Emergence of Social Media as Boundary Objects in Crisis Response: A Collective Action Perspective

During a series of recent natural catastrophes, social media has played an increasingly prominent and varied role in crisis response, ranging from facilitating the recruitment of volunteers during an earthquake to supporting spiritual recovery after a hurricane. In this paper, we propose that social media, beyond the conventional role of information support, can also function as boundary objects, which are crucial in spanning the boundaries among involved parties that inherently restrict crisis response. Using the 2011 Thailand floods as a case study, we present a conceptual model of the role of social media in enabling a coordinated response to disasters. More specifically, the model presents three distinct processes of emergence and the corresponding boundary objects enabled by the use of social media, which are important in bridging the cognitive, relational and social boundaries among the various entities involved in crisis response

'We seek revelation with our eyes' : engaging with school cultures through montage

This article approaches the issue of school culture[s] through Walter Benjamin’s project method of ‘montage.’ Five historians of education drawn from Europe and Latin America were presented with a series of school photographs and commentaries and were asked to use their knowledge and expertise to share their insights into past school culture[s]

Social Media as Boundary Objects in Crisis Response: A Collective Action Perspective

Master'sMASTER OF SCIENC

Being objective: communities of practice and the use of cultural artefacts in digital learning environments

Over the past decade there has been a dramatic increase in the volume of digital content created from museum, library and archive collections but research on how this material is actually used, particularly in digital learning environments, has fallen far behind the rate of supply. In order to address this gap, this thesis examines how communities of practice (CoPs) involved in the supply and use of digital artefacts in the Higher Education sector in the UK interact with content and what factors affect this process. It focuses on a case study involving the digitisation of Shakespeare collections used in postgraduate research, and the testing of use in a range of different learning environments. This produced a number of significant findings with implications for the HE and cultural sectors. Firstly, similar patterns of artefact use were found across all users suggesting there are generic ways in which everyone interacts with digital artefacts. However, distinct forms of use did emerge which correspond with membership of particular communities of practice. Secondly, members of a CoP appear to share a particular learning style and this is influenced by the learning environment. Finally, the research indicates that a mixed method for analysing and measuring use, piloted and tested in the case study, is possible