3D Face Recognition For Cows
Zusammenfassung
This paper presents a method to recognize cows using their 3D face point clouds. Face
is chosen because of the rigid structure of the skull compared to other parts. The 3D face point
clouds are acquired using a newly designed dual 3D camera setup. After registering the 3D faces to
a specific pose, the cow’s ID is determined by running Iterative Closest Point (ICP) method on the
probe against all the point clouds in the gallery. The root mean square error (RMSE) between the
ICP correspondences is used to identify the cows. The smaller the RMSE, the more likely that the
cow is from the same class. In a closed set of 32 cows with 5 point clouds per cow in the gallery, the
ICP recognition demonstrates an almost perfect identification rate of 99.53%.
- Vollständige Referenz
- BibTeX
Yeleshetty, D., Spreeuwers, L. & Li, Y.,
(2020).
3D Face Recognition For Cows.
In:
Brömme, A., Busch, C., Dantcheva, A., Raja, K., Rathgeb, C. & Uhl, A.
(Hrsg.),
BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group.
Bonn:
Gesellschaft für Informatik e.V..
(S. 163-171).
@inproceedings{mci/Yeleshetty2020,
author = {Yeleshetty, Deepak AND Spreeuwers, Luuk AND Li, Yan},
title = {3D Face Recognition For Cows},
booktitle = {BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group},
year = {2020},
editor = {Brömme, Arslan AND Busch, Christoph AND Dantcheva, Antitza AND Raja, Kiran AND Rathgeb, Christian AND Uhl, Andreas} ,
pages = { 163-171 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
author = {Yeleshetty, Deepak AND Spreeuwers, Luuk AND Li, Yan},
title = {3D Face Recognition For Cows},
booktitle = {BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group},
year = {2020},
editor = {Brömme, Arslan AND Busch, Christoph AND Dantcheva, Antitza AND Raja, Kiran AND Rathgeb, Christian AND Uhl, Andreas} ,
pages = { 163-171 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
| Dateien | Groesse | Format | Anzeige | |
|---|---|---|---|---|
| BIOSIG_2020_paper_22_update3.pdf | 2.735Mb | Öffnen |
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Mehr Information
ISBN: 978-3-88579-700-5
ISSN: 1617-5468
Datum: 2020
Sprache:
(en)
(en)
Typ: Text/Conference Paper

