Quantitative measures for classification of human upper body posture in video signal to improve online learning | Zendy

Marko Horvat | Zendy; Dora Doljanin | Zendy; Tomislav Jagušt | Zendy

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Quantitative measures for classification of human upper body posture in video signal to improve online learning

Author(s) -

Marko Horvat,

Dora Doljanin,

Tomislav Jagušt

Publication year - 2022

Publication title -

aip conference proceedings

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.177

H-Index - 75

eISSN - 1551-7616

pISSN - 0094-243X

DOI - 10.1063/5.0100044

Subject(s) - computer science , motion (physics) , orientation (vector space) , set (abstract data type) , artificial intelligence , quality (philosophy) , signal (programming language) , machine learning , software , computer vision , upper body , video quality , videoconferencing , online learning , pattern recognition (psychology) , multimedia , mathematics , medicine , metric (unit) , philosophy , operations management , geometry , physical strength , epistemology , economics , physical medicine and rehabilitation , programming language

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