<datafield tag="980" ind1=" " ind2=" ">
<subfield code="a">CHAPTER</subfield>
...</datafield>
<datafield tag="970" ind1=" " ind2=" ">
<subfield code="a">Chingovska_SPRINGER_2019/IDIAP</subfield>
...</datafield>
<datafield tag="245" ind1=" " ind2=" ">
<subfield code="a">Evaluation Methodologies for Biometric Presentation Attack Detection</subfield>
...</datafield>
<datafield tag="700" ind1=" " ind2=" ">
<subfield code="a">Chingovska, Ivana</subfield>
...</datafield>
<datafield tag="700" ind1=" " ind2=" ">
<subfield code="a">Mohammadi, Amir</subfield>
...</datafield>
<datafield tag="700" ind1=" " ind2=" ">
<subfield code="a">Anjos, André</subfield>
...</datafield>
<datafield tag="700" ind1=" " ind2=" ">
<subfield code="a">Marcel, Sébastien</subfield>
...</datafield>
<datafield tag="700" ind1=" " ind2=" ">
<subfield code="a">Marcel, Sébastien</subfield>
<subfield code="e">Ed.</subfield>
...</datafield>
<datafield tag="700" ind1=" " ind2=" ">
<subfield code="a">Nixon, Mark</subfield>
<subfield code="e">Ed.</subfield>
...</datafield>
<datafield tag="700" ind1=" " ind2=" ">
<subfield code="a">Fierrez, Julian</subfield>
<subfield code="e">Ed.</subfield>
...</datafield>
<datafield tag="700" ind1=" " ind2=" ">
<subfield code="a">Evans, Nicholas</subfield>
<subfield code="e">Ed.</subfield>
...</datafield>
<datafield tag="856" ind1="4" ind2="0">
<subfield code="i">EXTERNAL</subfield>
<subfield code="u">http://publications.idiap.ch/attachments/papers/2018/Chingovska_SPRINGER_2019.pdf</subfield>
<subfield code="x">PUBLIC</subfield>
...</datafield>
<datafield tag="711" ind1="2" ind2=" ">
<subfield code="a">Handbook of Biometric Anti-Spoofing</subfield>
...</datafield>
<datafield tag="260" ind1=" " ind2=" ">
<subfield code="c">2019</subfield>
<subfield code="b">Springer International Publishing</subfield>
...</datafield>
<datafield tag="773" ind1=" " ind2=" ">
<subfield code="z">978-3-319-92627-8</subfield>
...</datafield>
<datafield tag="856" ind1="4" ind2=" ">
<subfield code="u">https://www.springer.com/us/book/9783319926261</subfield>
<subfield code="z">URL</subfield>
...</datafield>
<datafield tag="024" ind1="7" ind2=" ">
<subfield code="a">10.1007/978-3-319-92627-8</subfield>
<subfield code="2">doi</subfield>
...</datafield>
<datafield tag="520" ind1=" " ind2=" ">
<subfield code="a">Presentation attack detection (PAD, also known as anti-spoofing) systems, regardless of the technique, biometric mode or degree of independence of external equipment, are most commonly treated as binary classification systems. The two classes that they differentiate are bona-fide and presentation attack samples. From this perspective, their evaluation is equivalent to the established evaluation standards for the binary classification systems. However, PAD systems are designed to operate in conjunction with recognition systems and as such can affect their performance. From the point of view of a recognition system, the presentation attacks are a separate class that they need to be detected and rejected. As the problem of presentation attack detection grows to this pseudo-ternary status, the evaluation methodologies for the recognition systems need to be revised and updated. Consequentially, the database requirements for presentation attack databases become more specific. The focus of this chapter is the task of biometric verification and its scope is three-fold: firstly, it gives the definition of the presentation attack detection problem from the two perspectives. Secondly, it states the database requirements for a fair and unbiased evaluation. Finally, it gives an overview of the existing evaluation techniques for presentation attacks detection systems and verification systems under presentation attacks.</subfield>
...</datafield>