INSTRUCTIONS FOR DOWNLOADING
ATVS-SLT DB
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Download license agreement,
send by email one signed and scanned copy to atvs uam.es according to the instructions given in point 2.
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Send an email to atvs uam.es, as follows:
Subject:
[DATABASE download: ATVS-SLT DB]
Body: Your name, e-mail, telephone
number, organization, postal mail, purpose for which you will use
the database, time and date at which you sent the email with the
signed license agreement.
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Once the email copy of the license
agreement has been received at ATVS, you will receive an email with a
username, a password, and a time slot to download the database.
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Download the database, for which you will need to provide the
authentication information given in step 4. After you finish the
download, please notify by email to atvs uam.es that you have
successfully completed the transaction.
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For more information, please contact: atvs uam.es
DESCRIPTION OF ATVS-SLT DB
The dataset comprises the on-line signature data of the 29
common users to the BiosecurID and the Biosecure databases. These two signature subsets were
acquired in a 15 month time span and present some unique features that make them especially
suited for aging evaluation of on-line signature recognition systems [PONE2013]. The
general time distribution of the different sessions of the database is shown in Fig. 1.
Figure 1. General time diagram of the different acquisition sessions that conform the ATVS On-Line Signature Long-Term DB.
It comprises 16 original signatures per user (29 users).
Samples were captured in 4 separate acquisition sessions (named BID1, BID2, BID3 and BID4 in Fig. 1).
The sessions were captured leaving a two month interval between them, in a controlled and supervised office-like scenario.
Users were asked to sign on a piece of paper, inside a grid that
marked the valid signing space, using an inking pen. The paper was placed on the Wacom Intuos 3
pen tablet that captured the time signals of each signature at a 100Hz sampling rate (trajectory
functions x and y with an accuracy of 0.25mm, pressure function p with a precision of 1024
pressure levels, and azimuth and altitute angles). All the dynamic information is stored in
separate text files following the format used in the first Signature Verification Competition,
SVC.
This dataset was captured 6 months after the BiosecurID acquisition campaign had finished (the time sequence of the two databases is shown in Fig. 1).
It comprises 30 original signatures per user (same 29 users as the BiosecurID subset) distributed in two acquisition sessions separated three months (named Bure1 and Bure2 in Fig. 1).
The 15 original samples corresponding to each session were captured in three groups of 5 consecutive signatures with an interval of around 15 minutes between groups (named in Fig. 1 Bure11-12-13 and Bure21-22-23, respectively).
The signature dataset was designed to be fully compatible with the
BiosecurID one. The acquisition scenario and protocol are almost identical: as in the BiosecurID
case, users had to sign using an inking pen on a piece of paper with a restricted space, placed
over the Wacom Intuos 3 pen tablet. The dynamic information stored is the same as in BiosecurID
and following also the SVC format.
The signatures are stored in text files following the format of the 2004 Signature Verification Competition (SVC), where:
The nomenclature followed to name the signature files is as follows: XXXX_sgYY.svc
XXXX: is the number of the user [1001, 1002, ... , 1029]
YY: is the number of the sample [1, 2, ... , 46]
The correspondence between signatures is as follows: XXXX_sgYY.svc
Signatures 1-4: BID1 (1st session of BiosecurID)
Signatures 5-8: BID2 (2nd session of BiosecurID)
Signatures 9-12: BID3 (3rd session of BiosecurID)
Signatures 13-16: BID4 (4th session of BiosecurID)
Signatures 17-31: Bure1 (1st session of Biosecure)
Signatures 32-46: Bure2 (2nd session of Biosecure)
REFERENCES
For further information on the database and on different applications where it has been used, we refer the reader to (all these articles are publicly
available in the publications section of the ATVS group webpage.)
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[PONE2013] J.Galbally, M. Martinez-Diaz and Julian Fierrez,
"Aging in Biometrics: An Experimental Analysis on On-Line Signature",
PLOS ONE, Vol. 8, n. 7, 2013 (DOI).
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[PAA2010] J. Fierrez, J. Galbally, J. Ortega-Garcia, M. R. Freire, F. Alonso-Fernandez, D. Ramos, D. T. Toledano, J. Gonzalez-Rodriguez, J. A. Siguenza, J. Garrido-Salas, E. Anguiano, G. Gonzalez-de-Rivera, R. Ribalda, M. Faundez-Zanuy, J. A. Ortega, V. Cardeñoso-Payo, A. Viloria, C. E. Vivaracho, Q. I. Moro, J. J. Igarza, J. Sanchez, I. Hernaez, C. Orrite-Uruñuela, F. Martinez-Contreras and J. J. Gracia-Roche,
"BiosecurID: A Multimodal Biometric Database",
Pattern Analysis and Applications, Vol. 13, n. 2, pp. 235-246, 2010.
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[PAMI2010] J. Ortega-Garcia, J. Fierrez, F. Alonso-Fernandez, J. Galbally, M. Freire, J. Gonzalez-Rodriguez, C.Garcia-Mateo, J.-L.Alba-Castro, E.Gonzalez-Agulla, E.Otero-Muras, S.Garcia-Salicetti, L.Allano, B.Ly-Van, B.Dorizzi, J.Kittler, T.Bourlai, N.Poh, F.Deravi, M.Ng, M.Fairhurst, J.Hennebert, A.Humm, M.Tistarelli, L.Brodo, J.Richiardi, A.Drygajlo, H.Ganster, F.M.Sukno, S.-K.Pavani, A.Frangi, L.Akarun and A.Savran,
"The Multi-Scenario Multi-Environment BioSecure Multimodal Database (BMDB)",
IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 32, n. 6, pp. 1097-1111, 2010.
Please remember to reference article [PONE2013] on any work made public, whatever the form, based directly or indirectly on any part of the ATVS-SSig DB.
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