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Abstract
The paper presents a camera-independent framework for detecting violations of two typical people movement rules that are in force in many public transit terminals: moving in the wrong direction or across designated lanes. Low-level image processing is based on object detection with Gaussian Mixture Models and employs Kalman filters with conflict resolving extensions for the object tracking. In order to allow an effective event recognition in a crowded environment, the algorithm for event detection is supplemented with the optical-flow based analysis in order to obtain pixel-level velocity characteristics. The proposed solution is evaluated with multi-camera, real-life recordings from an airport terminal. Results are discussed and compared with a traditional approach that does not include optical flow based direction of movement analysis.
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Details
- Category:
- Conference activity
- Type:
- materiały konferencyjne indeksowane w Web of Science
- Title of issue:
- 6th International Conference on Multimedia Communications, Services and Security (MCSS) strony 48 - 58
- Language:
- English
- Publication year:
- 2013
- Bibliographic description:
- Dalka P., Bratoszewski P..: Visual Detection of People Movement Rules Violation in Crowded Indoor Scenes, W: 6th International Conference on Multimedia Communications, Services and Security (MCSS), 2013, Springer-Verlag,.
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/978-3-642-38559-9_5
- Verified by:
- Gdańsk University of Technology
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