John W. Bastian

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Figure 1: Our method allows the user to recover the 3D shape of a selected object and insert copies of the object into the AR environment. ABSTRACT We present a method for estimating the 3D shape of an object from a sequence of images captured by a hand-held device. The method is well suited to augmented reality applications in that minimal user interaction(More)
Our ability to process information about an object's location in depth varies along the horizontal and vertical axes. These variations reflect functional specialisation of the cerebral hemispheres as well as the ventral/dorsal visual streams for processing stimuli located in near and far space. Prior research has demonstrated visual field superiorities for(More)
Automatic placement of surveillance cameras in arbitrary buildings is a challenging task, and also one that is essential for efficient deployment of large scale surveillance networks. Existing approaches for automatic camera placement are either limited to a small number of cameras, or constrained in terms of the building layouts to which they can be(More)
  • Simon J Del Fabbro, Drs Ken Hawick, Paul Coddington, John Bastian, Joseph Kuehn, Daniel Pooley
  • 2000
We attempt to develop a framework for the distributed processing of images, in particular, the remote accessing and manipulation of large geo-referenced images. The development is broken down into two diierent stages. The rst involves the development of a dataaow visual programming language (VPL) to allow users to develop programs out of chains of image(More)
  • John Bastian, Anton Van Den Hengel, Ken Hawick, Francis Vaughan
  • 2002
We have developed software for modelling the perceptual effects of lens distortion in a real-time immersive environment. Lens designers and wearers of corrective eye-wear will benefit by the softwares ability to visualise and obtain immediate feedback of the effects of a given lens design. This project involved extending the capabilities of lens distortion(More)
This paper describes a novel approach to the problem of recovering information from an image set by comparing the radiance of hypothesised point correspondences. Our algorithm is applicable to a number of problems in computer vision, but is explained particularly in terms of recovering geometry from an image set. It uses the idea of photo-consistency to(More)
We apply an online optimization process based on machine learning to the production of Bose-Einstein condensates (BEC). BEC is typically created with an exponential evaporation ramp that is optimal for ergodic dynamics with two-body s-wave interactions and no other loss rates, but likely sub-optimal for real experiments. Through repeated machine-controlled(More)
We propose a method to recover the structure of a compound scene from multiple silhouettes. Structure is expressed as a collection of 3D primitives chosen from a pre-defined library, each with an associated pose. This has several advantages over a volume or mesh representation both for estimation and the utility of the recovered model. The main challenge in(More)
We present a method for recovering the structure of a plant directly from a small set of widely-spaced images for automated analysis of phenotype. Structure recovery is more complex than shape estimation, but the resulting structure estimate is more closely related to phenotype than is a 3D geometric model. The method we propose is applicable to a wide(More)