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Robust Detection and Tracking Algorithm of Multiple Objects in Complex Scenes |
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PP: 2485-2490 |
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Author(s) |
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Hong-Yu Hu,
Zhao-Wei Qu,
Zhi-Hui Li,
Qing-Nian Wang,
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Abstract |
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| Detection and tracking of multiple targets in complex environment with an uncalibrated CCD camera is developed in this
paper. 1) A background initialization algorithm based on clustering is presented. All stable non-overlapping intervals in the temporal
training sequence of each pixel are located as possible backgrounds by slip window; then the background interval is obtained from
the classified data set of possible backgrounds by unsupervised clustering. 2) Moving multi-targets are tracked through integration of
the motion and shape features by Kalman filter model. In order to ensure the continuity and the stabilization, occlusion processing
is performed. The proposed approach is validated under real traffic scenes. Experimental results show that detection and tracking
algorithms are robust and adaptive and could be well applied in real-world. |
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