Generic active appearance models revisited
The proposed Active Orientation Models (AOMs) are generative models of facial shape and appearance. Their main differences with the well-known paradigm of Active Appearance Models (AAMs) are (i) they use a different statistical model of appearance, (ii) they are accompanied by a robust algorithm for...
| Main Authors: | , , , |
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| Format: | Article |
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Springer
2013
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| Online Access: | https://eprints.nottingham.ac.uk/31430/ |
| _version_ | 1848794199776821248 |
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| author | Tzimiropoulos, Georgios Alabort-i-Medina, Joan Zafeiriou, Stefanos Pantic, Maja |
| author_facet | Tzimiropoulos, Georgios Alabort-i-Medina, Joan Zafeiriou, Stefanos Pantic, Maja |
| author_sort | Tzimiropoulos, Georgios |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | The proposed Active Orientation Models (AOMs) are generative models of facial shape and appearance. Their main differences with the well-known paradigm of Active Appearance Models (AAMs) are (i) they use a different statistical model of appearance, (ii) they are accompanied by a robust algorithm for model fitting and parameter estimation and (iii) and, most importantly, they generalize well to unseen faces and variations. Their main similarity is computational complexity. The project-out version of AOMs is as computationally efficient as the standard project-out inverse compositional algorithm which is admittedly the fastest algorithm for fitting AAMs. We show that not only does the AOM generalize well to unseen identities, but also it outperforms state-of-the-art algorithms for the same task by a large margin. Finally, we prove our claims by providing Matlab code for reproducing our experiments. |
| first_indexed | 2025-11-14T19:12:24Z |
| format | Article |
| id | nottingham-31430 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:12:24Z |
| publishDate | 2013 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-314302020-05-04T20:20:54Z https://eprints.nottingham.ac.uk/31430/ Generic active appearance models revisited Tzimiropoulos, Georgios Alabort-i-Medina, Joan Zafeiriou, Stefanos Pantic, Maja The proposed Active Orientation Models (AOMs) are generative models of facial shape and appearance. Their main differences with the well-known paradigm of Active Appearance Models (AAMs) are (i) they use a different statistical model of appearance, (ii) they are accompanied by a robust algorithm for model fitting and parameter estimation and (iii) and, most importantly, they generalize well to unseen faces and variations. Their main similarity is computational complexity. The project-out version of AOMs is as computationally efficient as the standard project-out inverse compositional algorithm which is admittedly the fastest algorithm for fitting AAMs. We show that not only does the AOM generalize well to unseen identities, but also it outperforms state-of-the-art algorithms for the same task by a large margin. Finally, we prove our claims by providing Matlab code for reproducing our experiments. Springer 2013 Article PeerReviewed Tzimiropoulos, Georgios, Alabort-i-Medina, Joan, Zafeiriou, Stefanos and Pantic, Maja (2013) Generic active appearance models revisited. Lecture Notes in Computer Science, 7726 . pp. 650-663. ISSN 0302-9743 http://link.springer.com/chapter/10.1007/978-3-642-37431-9_50 doi:10.1007/978-3-642-37431-9_50 doi:10.1007/978-3-642-37431-9_50 |
| spellingShingle | Tzimiropoulos, Georgios Alabort-i-Medina, Joan Zafeiriou, Stefanos Pantic, Maja Generic active appearance models revisited |
| title | Generic active appearance models revisited |
| title_full | Generic active appearance models revisited |
| title_fullStr | Generic active appearance models revisited |
| title_full_unstemmed | Generic active appearance models revisited |
| title_short | Generic active appearance models revisited |
| title_sort | generic active appearance models revisited |
| url | https://eprints.nottingham.ac.uk/31430/ https://eprints.nottingham.ac.uk/31430/ https://eprints.nottingham.ac.uk/31430/ |