BMVA, British Machine Vision Association and Society for Pattern Recognition
 
 *** DO MANY CAMERAS MAKE LIGHT WORK? - Machine Vision in Photogrammetry
 
 One Day joint BMVA and Photogrammetric Society Technical Meeting in
 association with IEE/E4 to be held on 26th May 99 at British Institute
 of Radiology, 36 Portland Place, London.
 
 Chairpersons: Tim Ellis (City Uni); Stuart Robson (UCL)
  www.bmva.ac.uk/meetings
 10:30 Registration and coffee
 10:55 Introduction and welcome, Tim Ellis (City Uni); Stuart Robson
 (UCL)
 11:00 Aspects of camera self-calibration, Ian Reid, University of Oxford
 11:45 Gauge Methods in 3D Reconstruction,  Phil Mclauchlan, University
 	of Surrey
 12.15 Fast and Robust Integration of Multiple Range Models, Tim Niblett,
 	Turing Institute
 12.45 Surface-based Structure from Motion  Phil Mclauchlan, University
 	of Surrey
 13:15 Lunch
 14:00 Camera Calibration u a photogrammetric viewpoint, Tim Clarke, City
 	University
 14:30 An Integrated System for 3D Scene Reconstruction, Kia NG,
 	University of Leeds
 15:00 Tea
 15:30 Industrial Applications of Geometrically Indexed Panoramic Image
 	Archives,  Andy Deacon, As Built Solutions Ltd
 16:00 A Visualisation Methodology Suited to Engineering Measurement
 	Using Vision Metrology, Neil  Woodhouse, University College London
 16:30 Summary and discussion
 16:40 Closing remarks and finish
 
 REGISTRATION FORM: 26th May 1999 Meeting
 
 Please return this form to Richard Bowden, Dept M & ES, Brunel
 University, Uxbridge, UB8 3PH or via email to
 richard.bowden@brunel.ac.uk. The meeting is free to members of the BMVA,
 Photogrammetric Society or IEE but a charge of u20 is payable by
 non-members. A sandwich lunch is bookable on the day. When registering
 please enclose a cheque for the appropriate amount made payable to "The
 British Machine Vision Association".
 
 NAME:
 ADDRESS:
 TEL:
 BMVA MEMBER: YES/NO
 
 ***
 Title: Aspects of camera self-calibration
 Dr Ian Reid, Department of Engineering, University of Oxford.
 
 Camera calibration is a prerequisite for the computation of metric
 structure from any number of views of a scene. Although this can be
 achieved through the use of calibration grids or other accurately known
 scene structure, much interest in computer vision during the last six
 years has centred on methods for camera "self"-calibration.
 
 In this presentation I will give a tutorial introduction to the ideas
 behind camera self-calibration, and then, without an attempt to be
 comprehensive, I will discuss some recent results.
 
 Further information can be found at: http://www.robots.ox.ac.uk/~lav
 
 ***
 Title: Gauge Methods in 3D Reconstruction
 Phil Mclauchlan, Department of Electronic and Electrical Engineering,
 University of Surrey
 
 Bundle adjustment is a standard photogrammetric technique for optimizing
 the 3D reconstruction of a scene from multiple images. There is an
 inherent gauge (coordinate frame) ambiguity in 3D reconstruction that
 can seriously affect the convergence of bundle adjustment algorithms.
 Existing schemes for dealing with this ambiguity, both in photogrammetry
 and computer vision, have drawbacks. In those schemes, the results of
 bundle adjustment depend on the initially chosen coordinate frame, or on
 the order of the images, or both. Our scheme, which eliminates both
 these effects, involves first normalizing an initial reconstruction to
 achieve coordinate frame invariance, and then selecting gauge
 constraints on the parameter updates so that the normalization
 conditions applied are maintained to first order by the bundle
 adjustment iteration. The new approach applies to all the well-known 3D
 reconstruction models: projective, affine and Euclidean, and has been
 implemented for the reconstruction of 3D point & line features as well
 as planar surfaces.
 
 The normalization stage partially removes the gauge freedom, reducing
 the coordinate frame choice from a general 3D
 homography/affinity/similarity transformation to an orthogonal
 transformation, which is a 3x3 rotation in the affine & Euclidian cases,
 and a 4x4 orthogonal matrix in the projective case. In the projective
 case the normalisation relies on a general conjecture concerning
 projective vectors and matrices, which we strongly believe to be
 correct, based on extensive experimental evidence. The conjecture
 provides a new way to compute with projective quantities, allowing the
 effects of the choice of arbitrary scale factors and coordinate frame to
 be eliminated completely.
 
 Our results suggest that our new treatment of the coordinate frame
 ambiguity problem in bundle adjustment achieves faster and more stable
 convergence than existing methods.
 
 Further information can be found at:
 http://www.ee.surrey.ac.uk/EE/VSSP/3DVision/
 
 ***
 Title: Fast and Robust Integration of Multiple Range Models
 Tim Niblett, The Turing Institute
 
 The Turing Institute's C3D(R) 3-D capture system captures all-round
 models of 3-D objects. The models are obtained by "integrating" multiple
 range maps, with the range maps obtained from a pair of stereo images
 using a
 matching and photogrammetric procedures to produce the range map.
 
 The integration process within C3D involves:
 - Alignment (automatic) of the range maps into a common reference frame
 - Production of an intermediate voxel-based integrated 3-D model
 - Adjustment of the range maps and associated texture maps to provide a
 seamless join.
 - Output of an image-based model that can be used for accurate
 measurement or the production of various output formats (DXF, STL, VRML,
 etc).
 
 This talk will provide a brief overview of the various approaches to
 range-model integration that have been discussed in the literature. The
 process used by C3D will be described and related to these, with
 particular
 emphasis on robustness and speed. Some examples of the output of C3D's
 integration method will be given.
 
 For further information see: http://www.turing.gla.ac.uk/
 
 ***
 Title: Surface-based Structure from Motion
 Phil Mclauchlan, Department of Electronic and Electrical Engineering,
 University of Surrey
 
 The existing state-of-the art in structure-from-motion systems is the
 construction of sparse feature-based scene representations, e.g. from
 points and lines. The main drawback of such systems is the lack of
 surface information, which restricts their usefulness. Although it is
 possible to build surface modelling on top of the feature information,
 we have designed an algorithm that allows surface information to be
 built directly into the reconstruction algorithm, so that along with
 features, surface parameters may be computed. Constraints between
 surfaces and features, and between the surfaces themselves, may be
 incorporated.
 
 Our work may be seen as extending existing photogrammetric bundle
 adjustment algorithms to compute surface parameters. We employ the
 recursive partitioning algorithm, well-known in the photogrammetry
 community, to obtain efficient iterative updates of the reconstruction.
 Incorporating the surface constraints modifies the sparse structure of
 the normal equations, making it important to order the feature, surface
 and motion parameter blocks appropriately to achieve the best
 performance. We employ the Variable State Dimension Filter (VSDF) to
 effect both batch and recursive updates within the same framework.
 
 Further information can be found at:
 http://www.ee.surrey.ac.uk/EE/VSSP/3DVision/
 
 ***
 Title: Camera calibration - a photogrammetric viewpoint
 Dr. Tim Clarke and Dr. Xinchi Wang, School of Engineering, City
 University
 
 It can be argued that, with the possible exception of astronomers,
 photogrammetrists have derived the greatest quantity and quality of
 geometric information from images. For example images from low-level
 aerial surveys to remote sensing from satellites have produced maps of
 high quality for civil and military uses. As a result of such activity
 "camera calibration" (almost always meaning the estimation of the
 cameras interior parameters) has often been of national importance
 resulting in multi-million pound camera calibration facilities. On a
 practical level a wide range of calibration methods and models have been
 developed, some of these have become so standard that they have remained
 little changed over the past thirty or forty years. Never-the-less
 camera calibration is always a live topic and further advances are
 constantly being made.
 
 The developments in photogrammetry of aerial surveying for mapping are,
 of course, large and there are many aspects where machine vision
 techniques are used to automatically extract structures such as
 buildings, roads etc from such imagery. However, an area of closer
 overlap with machine vision is in what is variously called: close-range
 photogrammetry, videogrammetry, vision metrology, videometrics, or
 digital photogrammetry. Here there are a number of areas where the two
 communities can learn from each other, camera calibration is a good
 example. This tutorial will briefly review the development of
 photogrammetric camera calibration methods and models and give some
 practical examples of the calibration of a variety of cameras.
 
 For further information see: http://www.city.ac.uk/omc/
 
 ***
 Title: An Integrated System for 3D Scene Reconstruction
 Kia NG, Department of Computing, University of Leeds
 
  This talk will describe an integrated multi-sensory system for the
 acquisition and reconstruction of textured 3D scene models from laser
 range data and digital images, developed by an EU-ACTS project RESOLV.
 This approach has been implemented in a collection of algorithms and
 sensors within a prototype device for 3D reconstruction,
 known as the Environmental Sensor for Telepresence (EST). The EST can
 take the form of a push trolley or of an autonomous mobile platform. The
 Autonomous EST (AEST) has been designed to provide an integrated
 solution for automating the creation of complete models. Embedded
 software performs several functions, including triangulation of the
 range data, registration of video texture, registration and integration
 of data acquired from different capture points. Potential applications
 include facilities management for the construction industry and creating
 reality models to be used in general areas of virtual reality, for
 example, virtual studios, virtualised reality for content-related
 applications (e.g., CD-ROMs), social telepresence, architecture and
 others. I'll describe the main components of the EST/AEST, and presents
 some example results. The reconstructed model is encoded in VRML format
 so that it is
 possible to access and view the model via the World Wide Web.
 
 Further information about the project and example reconstruction can be
 found on the RESOLV web page, http://www.scs.leeds.ac.uk/resolv/
 
 ***
 Title: Industrial Applications of Geometrically Indexed Panoramic Image
 Archives.
 Andy deacon, As Built Solutions
 
 The talk will describe the use of large scale, geometrically indexed
 visual archives in the process industries. Applications include
 providing spatial data for the creation and update of 'as-built' 3D CAD
 models and providing a visual interface with facilities management
 systems.
 
 For further information see: http://www.absl.co.uk/
 
 ***
 Title: A visualisation methodology suited to engineering measurement
 using vision metrology
 Neil  Woodhouse, Department of Geomatic Engineering, University College
 London
 
 Techniques employing vision metrology to make high precision
 measurements of engineering structures for manufacturing purposes are in
 widespread usage within the aeronautic, automobile and shipbuilding
 industries. To extend the applicability of such techniques to
 engineering disciplines, where measurement is undertaken for monitoring
 or verification purposes, requires the rapid representation and
 visualisation of both spatial information and other engineering data.
 
 This presentation will introduce a generalised technique for the
 generation of computer graphics surface models from geometrically
 precise image networks taken for vision metrology purposes. The
 methodology incorporates
 a triangulation technique allied with robust testing routines that
 utilise image content including target location, occlusion and image
 texture information to provide a solution that is solely dependant on
 network
 geometry. End use examples taken from a variety of civil and mechanical
 engineering applications will be given.
 
 For further information see: http://www.ge.ucl.ac.uk