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231224s2013 xx |||||o 00| ||eng c |
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|a 10.1109/TPAMI.2012.190
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|a eng
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|a Cui, Yan
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Algorithms for 3D shape scanning with a depth camera
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| 264 |
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|c 2013
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|a Text
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|a ƒaComputermedien
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|a Date Completed 16.09.2013
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|a Date Revised 22.03.2013
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a We describe a method for 3D object scanning by aligning depth scans that were taken from around an object with a Time-of-Flight (ToF) camera. These ToF cameras can measure depth scans at video rate. Due to comparably simple technology, they bear potential for economical production in big volumes. Our easy-to-use, cost-effective scanning solution, which is based on such a sensor, could make 3D scanning technology more accessible to everyday users. The algorithmic challenge we face is that the sensor's level of random noise is substantial and there is a nontrivial systematic bias. In this paper, we show the surprising result that 3D scans of reasonable quality can also be obtained with a sensor of such low data quality. Established filtering and scan alignment techniques from the literature fail to achieve this goal. In contrast, our algorithm is based on a new combination of a 3D superresolution method with a probabilistic scan alignment approach that explicitly takes into account the sensor's noise characteristics
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|a Journal Article
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| 700 |
1 |
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|a Schuon, Sebastian
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Thrun, Sebastian
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Stricker, Didier
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Theobalt, Christian
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 35(2013), 5 vom: 23. Mai, Seite 1039-50
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|u http://dx.doi.org/10.1109/TPAMI.2012.190
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