Facial Landmarks Detector Learned by the Structured Output SVM

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F13%3A00211709" target="_blank" >RIV/68407700:21230/13:00211709 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007/978-3-642-38241-3_26" target="_blank" >http://link.springer.com/chapter/10.1007/978-3-642-38241-3_26</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-642-38241-3_26" target="_blank" >10.1007/978-3-642-38241-3_26</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Facial Landmarks Detector Learned by the Structured Output SVM

Popis výsledku v původním jazyce

We propose a principled approach to supervised learning of facial landmarks detector based on the Deformable Part Models (DPM). We treat the task of landmarks detection as an instance of the structured output classification. To learn the parameters of the detector we use the Structured Output Support Vector Machines algorithm. The objective function of the learning algorithm is directly related to the performance of the detector and controlled by the user-defined loss function, in contrast to the previous works. Our proposed detector is real-time on a standard computer, simple to implement and easily modifiable for detection of various set of landmarks. We evaluate the performance of our detector on a challenging ``Labeled Faces in the Wild'' (LFW) database. The empirical results show that our detector consistently outperforms two public domain implementations based on the Active Appearance Models and the DPM. We are releasing open-source code implementing our proposed detector along w

Název v anglickém jazyce

Facial Landmarks Detector Learned by the Structured Output SVM

Popis výsledku anglicky

We propose a principled approach to supervised learning of facial landmarks detector based on the Deformable Part Models (DPM). We treat the task of landmarks detection as an instance of the structured output classification. To learn the parameters of the detector we use the Structured Output Support Vector Machines algorithm. The objective function of the learning algorithm is directly related to the performance of the detector and controlled by the user-defined loss function, in contrast to the previous works. Our proposed detector is real-time on a standard computer, simple to implement and easily modifiable for detection of various set of landmarks. We evaluate the performance of our detector on a challenging ``Labeled Faces in the Wild'' (LFW) database. The empirical results show that our detector consistently outperforms two public domain implementations based on the Active Appearance Models and the DPM. We are releasing open-source code implementing our proposed detector along w

Druh

C - Kapitola v odborné knize

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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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

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název knihy nebo sborníku

Computer Vision, Imaging and Computer Graphics. Theory and Application

ISBN

978-3-642-38240-6

Počet stran výsledku

16

Strana od-do

383-398

Počet stran knihy

446

Název nakladatele

Springer

Místo vydání

Heidelberg

Kód UT WoS kapitoly

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