Emotion Recognition in video with Open CV and Cognitive Services API: A comparison.

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F17%3A63517246" target="_blank" >RIV/70883521:28140/17:63517246 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.daaam.info/Downloads/Pdfs/proceedings/proceedings_2017/164.pdf" target="_blank" >http://www.daaam.info/Downloads/Pdfs/proceedings/proceedings_2017/164.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2507/28th.daaam.proceedings.164" target="_blank" >10.2507/28th.daaam.proceedings.164</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Emotion Recognition in video with Open CV and Cognitive Services API: A comparison.

Popis výsledku v původním jazyce

Emotions are people&apos;s reactions to certain stimuli. Most common way to detect an emotion is by facial expression analysis. Machine learning algorithms combined with other artificial intelligence techniques have been developed in order to identify expressions found in images and videos. Support Vector Machines, along with Haar Cascade classifiers can be used for efficient emotion recognition. OpenCV, an open-source library for machine learning, makes it possible to develop computer-vision applications. Cognitive Services is a free set of APIs which easily integrate artificial intelligence in applications. In this paper a comparison between two implementations of Emotion Recognition algorithms, namely SVM and Cognitive Services API, was carried out to compare their performance. For this research, 500 tests were performed per experiment. The SVM implementation in OpenCV obtained the best performance, with an 84% accuracy, which can be boosted by increasing the sample size per emotion.

Název v anglickém jazyce

Emotion Recognition in video with Open CV and Cognitive Services API: A comparison.

Popis výsledku anglicky

Emotions are people&apos;s reactions to certain stimuli. Most common way to detect an emotion is by facial expression analysis. Machine learning algorithms combined with other artificial intelligence techniques have been developed in order to identify expressions found in images and videos. Support Vector Machines, along with Haar Cascade classifiers can be used for efficient emotion recognition. OpenCV, an open-source library for machine learning, makes it possible to develop computer-vision applications. Cognitive Services is a free set of APIs which easily integrate artificial intelligence in applications. In this paper a comparison between two implementations of Emotion Recognition algorithms, namely SVM and Cognitive Services API, was carried out to compare their performance. For this research, 500 tests were performed per experiment. The SVM implementation in OpenCV obtained the best performance, with an 84% accuracy, which can be boosted by increasing the sample size per emotion.

Druh

D - Stať ve sborníku

CEP obor

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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)

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

Annals of DAAAM International 2017, Volume 28

ISBN

978-3-902734-14-3

ISSN

2304-1382

e-ISSN

neuvedeno

Počet stran výsledku

6

Strana od-do

1185-1190

Název nakladatele

DAAAM International Vienna

Místo vydání

Vienna

Místo konání akce

Zadar

Datum konání akce

8. 11. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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