Analyzing human behavior in subspace: Dimensionality reduction + classification

Yang Liu, Zhonglei Gu, Tobey H. Ko

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

1 Citation (Scopus)


Automated detection of human behavior in a social setting has drawn considerable interests in recent years. In this working notes paper, we describe our system developed for human behavior analysis. The system is composed of two components: 1) a dimensionality reduction module that maps the original data to a subspace; and 2) a classifier module that classifies the test data based on the labels of training data in the learned subspace. The developed system is evaluated on the MediaEval 2018 Human Behavior Analysis Task.

Original languageEnglish
Title of host publicationWorking Notes Proceedings of the MediaEval 2018 Workshop
EditorsMartha Larson, Piyush Arora, Claire-Hélène Demarty, Michael Riegler, Benjamin Bischke, Emmanuel Dellandrea, Mathias Lux, Alastair Porter, Gareth J. F. Jones
Number of pages3
Publication statusPublished - Oct 2018
EventMediaEval 2018: Multimedia Benchmark Workshop - Sophia Antipolis, France
Duration: 29 Oct 201831 Oct 2018

Publication series

NameCEUR Workshop Proceedings
ISSN (Print)1613-0073


ConferenceMediaEval 2018: Multimedia Benchmark Workshop
CitySophia Antipolis
Internet address

Scopus Subject Areas

  • Computer Science(all)


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