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CEN/TS 17051:2017

Full body photography

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Kehtiv alates 02.06.2017
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CEN/TS 17051:2017
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Tüüp
Nimetus
02.06.2017
Põhitekst
This Technical Specification is intended to provide a Full Body Image Format for pattern recognition services and applications requiring the exchange of full body image data. Its typical applications include:
a)  human examination of high resolution full body images;
b)  human verification of identity based on full body images;
c)  computer automated full body identification;
d)  computer automated full body verification.
To enable applications on a wide variety of devices, including devices that have limited data storage, and to improve image recognition accuracy, ISO/IEC 19794 standards are followed regarding not only data format, but also scene constraints (lighting, pose, expression, etc.), photographic properties (positioning, camera focus, etc.), and digital image attributes (image resolution, image size, etc.).
A specific biometric profile for cross-border interoperability is required for full body photographs. Full body photography standardization is required to get good quality database images for identification and verification using video surveillance and other similar system generated images. At the moment, border guards take full body photographs using local practices for enrolment, verification, identification and watch list identification.
ISO 22311:2012 [10] specifies a common output file format that can be extracted from the video-surveillance contents collection systems to perform necessary processing. ISO/IEC 30137 [8] specifies data formats for storing, recording and transmitting biometric information acquired via a video surveillance system. The EN 62676 series [11] defines video surveillance systems for use in security applications.
The purpose of this Technical Specification is to provide expert guidance (i.e. best practices) for the photography of full body, especially when the resulting images are to be used for purposes of identification and verification, either by automated recognition systems or by human viewers.

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