Toward the automated extraction of accurate 3D models from close-range photogrammetric networks

Helen Papadaki; Stuart Robson; David P. Chapman; Neil G. Woodhouse

doi:10.1117/12.410882

22 December 2000 Toward the automated extraction of accurate 3D models from close-range photogrammetric networks

Helen Papadaki, Stuart Robson, David P. Chapman, Neil G. Woodhouse

Proceedings Volume 4309, Videometrics and Optical Methods for 3D Shape Measurement; (2000) https://doi.org/10.1117/12.410882
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States

Abstract

3D models are important products of measurement systems in a variety of applications such as archaeology, medicine, architecture and engineering. In order to be appropriate to the end user, such object models must comply with certain accuracy standards. To achieve both accuracy and object coverage with a close range photogrammetric approach often requires a convergent image network in combination with retro reflective targets or some form of projected pattern. Retro-reflective targets alone can only provide sparse data. However, by optimizing image acquisition to record both targets and natural surface texture information, proven high accuracy retro reflective target image measurement can be combined with a wealth of automated image analysis algorithms developed by both photogrammetric and machine vision communities.

Citation Download Citation

Helen Papadaki, Stuart Robson, David P. Chapman, and Neil G. Woodhouse "Toward the automated extraction of accurate 3D models from close-range photogrammetric networks", Proc. SPIE 4309, Videometrics and Optical Methods for 3D Shape Measurement, (22 December 2000); https://doi.org/10.1117/12.410882

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