Learning shape priors for single view reconstruction

In this paper, we aim to reconstruct free-from 3D models from a single view by learning the prior knowledge of a specific class of objects. Instead of heuristically proposing specific regularities and defining parametric models as previous research, our shape prior is learned directly from existing 3D models under a framework based on the Gaussian Process Latent Variable Model (GPLVM). The major contributions of the paper include: 1) a probabilistic framework for prior-based reconstruction we propose, which requires no heuristic of the object, and can be easily generalized to handle various categories of 3D objects, and 2) an attempt at automatic reconstruction of more complex 3D shapes, like human bodies, from 2D silhouettes only. Qualitative and quantitative experimental results on both synthetic and real data demonstrate the efficacy of our new approach. ©2009 IEEE.

The Bayesian view of extreme events

The Bayesian perspective of designing for the consequences of hazard is discussed. Structural engineers should be educated in Bayesian theory and its underlying philosophy, and about the centrality to the prediction problem of the predictive distribution. The primary contribution that Bayesianism can make to the debate about extreme possibilities is its clarification of the language of and thinking about risk. Frequentist methodologies are the wrong approach to the decisions that engineers need to make, decisions that involve assessments of abstract future possibilities based on incomplete and abstract information.

Beyond 2D-grids: A dependence maximization view on image browsing

Ideally, one would like to perform image search using an intuitive and friendly approach. Many existing image search engines, however, present users with sets of images arranged in some default order on the screen, typically the relevance to a query, only. While this certainly has its advantages, arguably, a more flexible and intuitive way would be to sort images into arbitrary structures such as grids, hierarchies, or spheres so that images that are visually or semantically alike are placed together. This paper focuses on designing such a navigation system for image browsers. This is a challenging task because arbitrary layout structure makes it difficult - if not impossible - to compute cross-similarities between images and structure coordinates, the main ingredient of traditional layouting approaches. For this reason, we resort to a recently developed machine learning technique: kernelized sorting. It is a general technique for matching pairs of objects from different domains without requiring cross-domain similarity measures and hence elegantly allows sorting images into arbitrary structures. Moreover, we extend it so that some images can be preselected for instance forming the tip of the hierarchy allowing to subsequently navigate through the search results in the lower levels in an intuitive way. Copyright 2010 ACM.

A clinical system for three-dimensional extended-field-of-view ultrasound.

OBJECTIVE: This work is concerned with the creation of three-dimensional (3D) extended-field-of-view ultrasound from a set of volumes acquired using a mechanically swept 3D probe. 3D volumes of ultrasound data can be registered by attaching a position sensor to the probe; this can be an inconvenience in a clinical setting. A position sensor can also cause some misalignment due to patient movement and respiratory motion. We propose a combination of three-degrees-of-freedom image registration and an unobtrusively integrated inertial sensor for measuring orientation. The aim of this research is to produce a reliable and portable ultrasound system that is able to register 3D volumes quickly, making it suitable for clinical use. METHOD: As part of a feasibility study we recruited 28 pregnant females attending for routine obstetric scans to undergo 3D extended-field-of-view ultrasound. A total of 49 data sets were recorded. Each registered data set was assessed for correct alignment of each volume by two independent observers. RESULTS: In 77-83% of the data sets more than four consecutive volumes registered. The successful registration relies on good overlap between volumes and is adversely affected by advancing gestational age and foetal movement. CONCLUSION: The development of reliable 3D extended-field-of-view ultrasound may help ultrasound practitioners to demonstrate the anatomical relation of pathology and provide a convenient way to store data.

Linking business ecosystem lifecycle with platform strategy: A triple view of technology, application and organisation

This paper explores platform strategies along the business ecosystem lifecycle (BELC), based on a multiple-case study. Developing observations on platform strategies from a firm level to a business ecosystem level, the study investigates the issue of platform strategy through three views, respectively technology, application and organisation. As a result, a general evolutional pattern of platform strategy along the BELC is identified, where an open strategy emerges at the birth and expansion phases, then a dominating strategy rises at the authority phase, and finally the opportunistic strategy takes over at the renewal phase. This paper connects the core firms in the business ecosystem with the evolutionary platform strategies. Copyright © 2013 Inderscience Enterprises Ltd.