| DOI | Resolve DOI: https://doi.org/10.1007/s00138-013-0579-9 |
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| Author | Search for: Salazar, A.; Search for: Wuhrer, S.; Search for: Shu, C.1; Search for: Prieto, F. |
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| Affiliation | - National Research Council of Canada
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| Format | Text, Article |
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| Abstract | We consider the problem of computing accurate point-to-point correspondences among a set of human face scans with varying expressions. Our fully automatic approach does not require any manually placed markers on the scan. Instead, the approach learns the locations of a set of landmarks present in a database and uses this knowledge to automatically predict the locations of these landmarks on a newly available scan. The predicted landmarks are then used to compute point-to-point correspondences between a template model and the newly available scan. To accurately fit the expression of the template to the expression of the scan, we use as template a blendshape model. Our algorithm was tested on a database of human faces of different ethnic groups with strongly varying expressions. Experimental results show that the obtained point-to-point correspondence is both highly accurate and consistent for most of the tested 3D face models. © 2013 Springer-Verlag Berlin Heidelberg. |
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| Publication date | 2013 |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| NPARC number | 21270717 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | c44a3083-a9b7-4bf4-b60a-4081e5b4439b |
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| Record created | 2014-02-17 |
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| Record modified | 2020-04-22 |
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