Speaker Bio:
Clive Fraser is currently a Principal Consultant for the Photometrix Division of Geodetic Systems, as well as being a Program Science Director (P/T) in the Cooperative Research Centre for Spatial Information, and an Honorary Professorial Fellow in the Dept. of Infrastructure Engineering at the University of Melbourne. Prof. Fraser’s particular areas of research interest lie in digital close-range photogrammetry, including 3D forensic analysis and accident reconstruction, industrial measurement systems, and the metric exploitation of high-resolution satellite imagery. In recognition of his academic and professional work he has earned numerous international awards and has authored more than 380 scientific publications.
AUTOMATED, TARGETLESS Photogrammetric measurement: POTENTIAL AND LIMITATIONS
Dr Clive S. Fraser
Photometrix Div. of Geodetic Systems, Inc
Melbourne, Australia
ph. +61 411 453 726
ABSTRACT:
Close-range photogrammetry is now a widely-adopted tool for a host of 3D measurement tasks across areas as diverse as industrial metrology, forensics and heritage recording. Whereas with industrial and engineering applications the utilisation of targets is near universal, the adoption of automated, targetless orientation and object reconstruction is becoming increasingly more widespread in other application domains. This naturally poses the question of why so-called Structure-from-Motion (SfM) or Feature-Based Matching (FBM) techniques for automatic photogrammetric measurement are yet to employed to any significant extent in large-scale metrology, in spite of the obviously appealing prospect of dispensing with artificial signalisation, be it through physical targets or projection schemes. This presentation reviews the development of targetless, automated photogrammetric measurement, which has been given extra impetus through the introduction of drones/UAVs as camera platforms. Prospects for adoption of SfM approaches in industrial and engineering measurement are then discussed, with particular emphasis upon the broader requirements of 3D feature point measurement. Although the potential of automated targetless photogrammetry is significant, there are nevertheless many limitations to adoption, not least in the area of accuracy, feature point identification and operational constraints applying to drones.
