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- W2092742694 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." @default.
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- W2092742694 date "2000-12-22" @default.
- W2092742694 modified "2023-09-23" @default.
- W2092742694 title "<title>Toward the automated extraction of accurate 3D models from close-range photogrammetric networks</title>" @default.
- W2092742694 doi "https://doi.org/10.1117/12.410882" @default.
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