Flexible human behavior analysis framework for video surveillance applications

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

Research output: Contribution to journalArticleAcademicpeer-review

20 Citations (Scopus)
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Abstract

We study a flexible framework for semantic analysis of human motion from surveillance video. Successful trajectory estimation and human-body modeling facilitate the semantic analysis of human activities in video sequences. Although human motion is widely investigated, we have extended such research in three aspects. By adding a second camera, not only more reliable behavior analysis is possible, but it also enables to map the ongoing scene events onto a 3D setting to facilitate further semantic analysis. The second contribution is the introduction of a 3D reconstruction scheme for scene understanding. Thirdly, we perform a fast scheme to detect different body parts and generate a fitting skeleton model, without using the explicit assumption of upright body posture. The extension of multiple-view fusion improves the event-based semantic analysis by 15%–30%. Our proposed framework proves its effectiveness as it achieves a near real-time performance (13–15 frames/second and 6–8 frames/second) for monocular and two-view video sequences.
Original languageEnglish
Pages (from-to)920121-1/9
JournalInternational Journal of Digital Multimedia Broadcasting
Volume2010
DOIs
Publication statusPublished - 2010

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