19 January 2009 Multi-level human motion analysis for surveillance applications
Author Affiliations +
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).
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Weilun Lao, Jungong Han, Peter H. N. de With, "Multi-level human motion analysis for surveillance applications", Proc. SPIE 7257, Visual Communications and Image Processing 2009, 72570C (19 January 2009); doi: 10.1117/12.807320; https://doi.org/10.1117/12.807320

Back to Top