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ISVC
2005
Springer

Mining Paths of Complex Crowd Scenes

9 years 3 months ago
Mining Paths of Complex Crowd Scenes
The Ambient Intelligence (AmI) paradigm requires a robust interpretation of people actions and behaviour and a way for automatically generating persistent spatial-temporal models of recurring events. This paper describes a relatively inexpensive technique that does not require the use of conventional trackers to identify the main paths of highly cluttered scenes, approximating them with spline curves. An AmI system could easily make use of the generated model to identify people who do not follow prefixed paths and warn them. Security, safety, rehabilitation are potential application areas. The model is evaluated against new data of the same scene.
Beibei Zhan, Paolo Remagnino, Sergio A. Velastin
Added 28 Jun 2010
Updated 28 Jun 2010
Type Conference
Year 2005
Where ISVC
Authors Beibei Zhan, Paolo Remagnino, Sergio A. Velastin
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