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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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Informacje szczegółowe
- Kategoria:
- Aktywność konferencyjna
- Typ:
- materiały konferencyjne indeksowane w Web of Science
- Tytuł wydania:
- 6th International Conference on Multimedia Communications, Services and Security (MCSS) strony 48 - 58
- Język:
- angielski
- Rok wydania:
- 2013
- Opis bibliograficzny:
- 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:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1007/978-3-642-38559-9_5
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 107 razy