ICDAR 2021 Competition on On-Line Signature Verification (SVC2021_EvalDB)

2021-05-28 (v. 1)

Contact author

Ruben Tolosana

Biometrics and Data Pattern Analytics Lab (BiDA Lab), UAM

ruben.tolosana@uam.es

+34914977506

+34914977506

You can cite this dataset as: Ruben Tolosana, ICDAR 2021 Competition on On-Line Signature Verification (SVC2021_EvalDB) ,1,ID:SVC2021_EvalDB_1,URL:https://tc11.cvc.uab.es/datasets/SVC2021_EvalDB_1

Dataset Information

Dataset URL

https://github.com/BiDAlab/SVC2021_EvalDB

Keywords

Handwriting; On-Line Signature; Biometrics; SVC 2021; SVC On-Going

Description

 

SVC On-Going Competition

 

 

 

 

 

 

 

 

 

The SVC2021_EvalDB database is a novel database specifically acquired for the ICDAR 2021 Competition on On-Line Signature Verification (SVC 2021) and also used in SVC On-Going Competition. Two acquisition scenarios are considered: office and mobile scenarios.

  • Office scenario: on-line signatures from 75 total subjects were acquired using a Wacom STU-530 device with the stylus as writing input. Regarding the acquisition protocol, the device was placed on a desktop and subjects were able to rotate it in order to feel comfortable with the writing position. It is important to highlight that the subjects considered in the acquisition of SVC2021_EvalDB are different compared to the ones considered in the DeepSignDB database. Signatures were collected in two separated sessions with a time gap between them of at least 1 week. For each subject, there are 8 total genuine signatures (4 signatures/session) and 16 skilled forgeries (8 signatures/type) performed by four different subjects in two different sessions. Regarding the skilled forgeries, both static and dynamic forgeries were considered in the first and second acquisition sessions, respectively. Information related to X and Y spatial coordinates, pressure, and timestamp is recorded for the Wacom device. In addition, pen-up trajectories are also available.

  • Mobile scenario: on-line signatures from 119 total subjects were acquired using the same acquisition framework considered in MobileTouchDB. Regarding the acquisition protocol, we implemented an Android App and uploaded it to the Play Store in order to study an unsupervised mobile scenario. This way all subjects could download the App and use it on their own devices without any kind of supervision, simulating a practical scenario in which subjects can generate touchscreen on-line signatures in any possible scenario, e.g., standing, sitting, walking, indoors, outdoors, etc. As a result, 94 different smartphone models from 16 different brands were collected during the acquisition. Regarding the acquisition protocol, between four and six separated sessions in different days were considered with a total time gap between the first and last session of at least 3 weeks. For each subject, there are at least 8 total genuine signatures (2 signatures/session) and 16 skilled forgeries (8 signatures/type) performed by four different subjects. Regarding the skilled forgeries, both static and dynamic forgeries were considered, similar to the office scenario. Information related to X and Y spatial coordinates, and timestamp is recorded for all devices. Pen-up information is not available in this case.

 

Reference

R. Tolosana, R. Vera-Rodriguez, C. Gonzalez-Garcia, et al., “ICDAR 2021 Competition on On-Line Signature Verification”, in Proc. International Conference on Document Analysis and Recognition, ICDAR, Lausanne, Switzerland, 2021.  

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