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Visual Tracking of Objects via Rule-based Multiple Hypothesis Tracking
Date
2008-04-22
Author
Ergezer, Hamza
Leblebicioğlu, Mehmet Kemal
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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In this paper, one of the most crucial step of a visual surveillance system is presented. To track the multiple objects in the scene, multiple hypothesis tracking is combined with the fuzzy logic. Mixture of Gaussians method has been used to detect the moving objects in the video, which is taken from a static camera. Kalman filter has been utilized to estimate the next state of the objects. After the estimation, current measurements have been compared with the estimated features by utilizing fuzzy rules. The proposed method has been tested for both single and multiple camera configurations.
Subject Keywords
Radar tracking
,
Kalman filters
,
Target tracking
,
Estimation
,
Cameras
,
Real time systems
,
Visualization
URI
https://hdl.handle.net/11511/47810
DOI
https://doi.org/10.1109/siu.2008.4632722
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
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BibTeX
H. Ergezer and M. K. Leblebicioğlu, “Visual Tracking of Objects via Rule-based Multiple Hypothesis Tracking,” 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/47810.