Analyzing human behavior in subspace: Dimensionality reduction + classification

Yang LIU, Zhonglei Gu, Tobey H. Ko

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

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. Copyright held by the owner/author(s).

Original languageEnglish
JournalCEUR Workshop Proceedings
Volume2283
Publication statusPublished - 2018
Event2018 Working Notes Proceedings of the MediaEval Workshop, MediaEval 2018 - Sophia Antipolis, France
Duration: 29 Oct 201831 Oct 2018

Scopus Subject Areas

  • Computer Science(all)

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