Multi-level human motion analysis for surveillance applications

W. Lao, Jungong Han, P.H.N. With, de

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)


In this paper, we study a flexible framework for semantic analysis of human motion from a monocular surveillance video. Successful trajectory estimation and human-body modeling facilitate the semantic analysis of human activities in video sequences. As a first contribution, we propose a flexible framework that enables automatic analysis of human behavior and semantic events. It can be utilized in surveillance applications with four-level analysis results. The second contribution is the introduction of a 3-D reconstruction scheme for scene understanding. The total framework consists of four processing levels: (1) a pre-processing level including background modeling and multiple-person detection, (2) an object-based level performing trajectory estimation and posture classification, (3) an event-based level for semantic analysis and (4) a visualization level including camera calibration and 3-D scene reconstruction. Our proposed framework was evaluated and proved its effectiveness as it achieves a near real-time performance (6-8 frames/second).
Original languageEnglish
Title of host publicationProceedings Visual Communications and Image Processing, 20 January 2009, San Jose, California
EditorsM. Rabbani, R.L. Stevenson
Place of PublicationBellingham
ISBN (Print)978-0-8194-7507-7
Publication statusPublished - 2009

Publication series

NameProceedings of SPIE
ISSN (Print)0277-786X


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