Dataset Restricted Access
MOBIO
McCool, Chris;
Marcel, Sébastien;
Hadid, Abdenour;
Pietikäinen, Matti;
Matějka, Pavel;
Černocký, Jan;
Poh, Norman;
Kittler, Josef;
Larcher, Anthony;
Lévy, Christophe;
Matrouf, Driss;
Bonastre, Jean-François;
Tresadern, Phil;
Cootes, Timothy
DCAT Export
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<dct:title>MOBIO</dct:title>
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<dcat:keyword>biometrics</dcat:keyword>
<dcat:keyword>face recognition</dcat:keyword>
<dcat:keyword>speaker recognition</dcat:keyword>
<dcat:keyword>mobile phones</dcat:keyword>
<dcat:keyword>RGB</dcat:keyword>
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<dct:description><p><strong>MOBIO is a dataset for mobile face and speaker recognition. The dataset consists of bi-modal (audio and video) data taken from 150 people. The dataset has a female-male ratio of nearly 1:2 (99 males and 51 females) and was collected from August 2008 until July 2010 in six different sites from five different countries. This led to a diverse bi-modal dataset with both native and non-native English speakers.</strong></p> <p>In total 12 sessions were captured for each client: 6 sessions for Phase I and 6 sessions for Phase II. The Phase I data consists of 21 questions with the question types ranging from: Short Response Questions, Short Response Free Speech, Set Speech, and Free Speech. The Phase II data consists of 11 questions with the question types ranging from:&nbsp; Short Response Questions, Set Speech, and Free Speech. A more detailed description of the questions asked of the clients is provided below.</p> <p>The database was recorded using two mobile devices: a mobile phone and a laptop computer. The mobile phone used to capture the database was a NOKIA N93i mobile while the laptop computer was a standard 2008 MacBook. The laptop was only used to capture part of the first session, this first session consists of data captured on both the laptop and the mobile phone.</p> <p>&nbsp;</p> <p><strong>Detailed Description of Questions</strong></p> <p><em>Please note that the answers to the Short Response Free Speech and Free Speech questions DO NOT necessarily relate to the question as the sole purpose is to have the subject speaking free speech, therefore, the answers to ALL of these questions are assumed to be false.</em></p> <p><strong>1. Short Response Questions</strong><br> The short response questions consisted of five pre-defined questions, which were:</p> <ul> <li>What is your name? &ndash; the user supplies their fake name</li> <li>What is your address? &ndash; the user supplies their fake address</li> <li>What is your birthdate? &ndash; the user supplies their fake birthdate</li> <li>What is your license number? &ndash; the user supplied their fake ID card number (the same for each person)</li> <li>What is your credit card number? &ndash; the user supplies their fake Card number</li> </ul> <p><strong>2. Short Response Free Speech</strong><br> There were five random questions taken form a list of 30-40 questions. The user had to answer these questions by speaking for approximately 5 seconds of recording (sometimes more and sometimes less).</p> <p><strong>3. Set Speech</strong><br> The users were asked to read pre-defined text out aloud. This text was designed to take longer than 10 seconds to utter and the participants were allowed to correct themselves while reading these paragraphs.<br> The text that was read was:</p> <blockquote>I have signed the MOBIO consent form and I understand that my biometric data is being captured for a database that might be made publicly available for research purposes.</blockquote> <blockquote>I understand that I am solely responsible for the content of my statements and my behaviour.</blockquote> <blockquote>I will ensure that when answering a question I do not provide any personal information in response to any question.</blockquote> <p><strong>4. Free Speech</strong><br> The free speech session consisted of 10 random questions from a list of approximately 30 questions. The answers to each of these questions took approximately 10 seconds (sometimes less and sometimes more).</p> <p>&nbsp;</p> <p><strong>Acknowledgements</strong></p> <p>Elie Khoury, Laurent El-Shafey, Christopher McCool, Manuel G&uuml;nther, S&eacute;bastien Marcel, &ldquo;Bi-modal biometric authentication on mobile phones in challenging conditions&rdquo;, Image and Vision Computing Volume 32, Issue 12, 2014.<br> <a href="https://doi.org/10.1016/j.imavis.2013.10.001">10.1016/j.imavis.2013.10.001</a><br> <a href="https://publications.idiap.ch/index.php/publications/show/2689">https://publications.idiap.ch/index.php/publications/show/2689</a></p></dct:description>
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1,898
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| Views | 1,898 |
| Downloads | 1,116 |
| Data volume | 8.4 TB |
| Unique views | 1,451 |
| Unique downloads | 215 |
Indexed in
- Publication date:
- November 12, 2020
- DOI:
-
- Keyword(s):
- biometrics face recognition speaker recognition mobile phones RGB
- Grants:
-
European Commission:
-
MOBIO - Mobile Biometry (214324)
-
BBFOR2 - Bayesian Biometrics For Forensics (238803)
- BEAT - Biometrics Evaluation and Testing (284989)
-
MOBIO - Mobile Biometry (214324)
- Related identifiers:
- Documented by
- 10.1016/j.imavis.2013.10.001 (Journal article)
- Communities: