Dogface Detection and Localization of Dogface's Landmarks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F19%3A63520502" target="_blank" >RIV/70883521:28140/19:63520502 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-91189-2_46" target="_blank" >http://dx.doi.org/10.1007/978-3-319-91189-2_46</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-91189-2_46" target="_blank" >10.1007/978-3-319-91189-2_46</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Dogface Detection and Localization of Dogface's Landmarks

Popis výsledku v původním jazyce

The paper deals with an approach for a reliable dogface detection in an image using the convolutional neural networks. Two detectors were trained on a dataset containing 8351 real-world images of different dog breeds. The first detector achieved the average precision equal to 0.79 while running real-time on single CPU, the second one achieved the average precision equal to 0.98 but more time for processing is necessary. Consequently, the facial landmark detector using the cascade of regressors was proposed based on those, which are commonly used in human face detection. The proposed lgorithm is able to detect dog’s eyes, a muzzle, a top of the head and inner bases of the ears with the 0.05 median location error normalized by the inter-ocular distance. The proposed two-step technique – a dogface detection with following facial landmark detector - could be utilized for a dog breeds dentification and consequent auto-tagging and image searches. The paper demonstrates a real-world application of the proposed technique – a successful supporting system for taking pictures of dogs facing the camera.

Název v anglickém jazyce

Dogface Detection and Localization of Dogface's Landmarks

Popis výsledku anglicky

The paper deals with an approach for a reliable dogface detection in an image using the convolutional neural networks. Two detectors were trained on a dataset containing 8351 real-world images of different dog breeds. The first detector achieved the average precision equal to 0.79 while running real-time on single CPU, the second one achieved the average precision equal to 0.98 but more time for processing is necessary. Consequently, the facial landmark detector using the cascade of regressors was proposed based on those, which are commonly used in human face detection. The proposed lgorithm is able to detect dog’s eyes, a muzzle, a top of the head and inner bases of the ears with the 0.05 median location error normalized by the inter-ocular distance. The proposed two-step technique – a dogface detection with following facial landmark detector - could be utilized for a dog breeds dentification and consequent auto-tagging and image searches. The paper demonstrates a real-world application of the proposed technique – a successful supporting system for taking pictures of dogs facing the camera.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

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

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název statě ve sborníku

Advances in Intelligent Systems and Computing, Volume 764

ISBN

978-3-319-91188-5

ISSN

2194-5357

e-ISSN

2194-5365

Počet stran výsledku

12

Strana od-do

465-476

Název nakladatele

Springer Verlag

Místo vydání

Berlín

Místo konání akce

Zlín

Datum konání akce

25. 4. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000460247600046