Dominant subject recognition by Bayesian learning

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00355205" target="_blank" >RIV/68407700:21230/21:00355205 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1109/FG52635.2021.9666979" target="_blank" >https://doi.org/10.1109/FG52635.2021.9666979</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/FG52635.2021.9666979" target="_blank" >10.1109/FG52635.2021.9666979</a>

Result language

angličtina

Original language name

Dominant subject recognition by Bayesian learning

Original language description

We tackle the problem of dominant subject recognition (DSR), which aims at identifying the faces of the subject whose faces appear most frequently in a given collection of images. We propose a simple algorithm solving the DSR problem in a principled way via Bayesian learning. The proposed algorithm has complexity quadratic in the number of detected faces, and it provides labeling of images along with an accurate estimate of the prediction confidence. The prediction confidence permits using the algorithm in semiautomatic mode when only a subset of images with uncertain labels are corrected manually. We demonstrate on a challenging IJB-B database, that the algorithm significantly reduces the number of images that need to be manually annotated to get the perfect performance of face verification and face identification systems using the face database created by the method.

Czech name

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Czech description

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Type

D - Article in proceedings

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

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2021

Confidentiality

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

Article name in the collection

Proc. of the 16th IEEE International Conference on Automatic Face and Gesture Recognition, 2021 (FG 2021)

ISBN

978-1-6654-3176-7

ISSN

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e-ISSN

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Number of pages

5

Pages from-to

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Publisher name

IEEE Computer Society Press

Place of publication

Los Alamitos

Event location

Jodhpur

Event date

Dec 15, 2021

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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