Özet:

In this paper, we present a novel method to detect and classify moving objects from surveillance videos that are obtained from a moving camera. In our method, we first estimate the camera motion by interpreting the movement of interest points in the scene. Then, we eliminate the camera motion and find candidate regions that belong to the moving objects. Considering these regions as priors, we apply an efficient segmentation algorithm to obtain accurate object boundaries for the moving objects. Finally, we classify the detected objects as people, vehicle, or others using some morphological features and the velocity vectors of moving objects. The evaluation of the proposed approach on our surveillance dataset shows that our approach is very effective for determining the classes of moving objects in a moving camera setting.

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