Multi-Frame Labeled Faces Database: Towards Face Super-Resolution from Realistic Video Sequences

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F20%3APU137491" target="_blank" >RIV/00216305:26220/20:PU137491 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/2076-3417/10/20/7213" target="_blank" >https://www.mdpi.com/2076-3417/10/20/7213</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/app10207213" target="_blank" >10.3390/app10207213</a>

Result language

angličtina

Original language name

Multi-Frame Labeled Faces Database: Towards Face Super-Resolution from Realistic Video Sequences

Original language description

Forensically trained facial reviewers are still considered as one of the most accurate approaches for person identification from video records. The human brain can utilize information, not just from a single image, but also from a sequence of images (i.e., videos), and even in the case of low-quality records or a long distance from a camera, it can accurately identify a given person. Unfortunately, in many cases, a single still image is needed. An example of such a case is a police search that is about to be announced in newspapers. This paper introduces a face database obtained from real environment counting in 17,426 sequences of images. The dataset includes persons of various races and ages and also different environments, different lighting conditions or camera device types. This paper also introduces a new multi-frame face super-resolution method and compares this method with the state-of-the-art single-frame and multi-frame super-resolution methods. We prove that the proposed method increases the quality of face images, even in cases of low-resolution low-quality input images, and provides better results than single-frame approaches that are still considered the best in this area. Quality of face images was evaluated using several objective mathematical methods, and also subjective ones, by several volunteers. The source code and the dataset were released and the experiment is fully reproducible.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Applied Sciences - Basel

ISSN

2076-3417

e-ISSN

—

Volume of the periodical

10

Issue of the periodical within the volume

20

Country of publishing house

CH - SWITZERLAND

Number of pages

27

Pages from-to

1-27

UT code for WoS article

000585125700001

EID of the result in the Scopus database

2-s2.0-85092787115