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From this experiment, we can conclude that the proposed moving object detection algorithm is able to exactly detect the moving object using only 20% sampled measurements in the indoor video sequences.
What they didn't say: It is packed with so much accident-avoidance technology, including backup collision intervention, distance control assist, around view monitor with moving object detection and blind spot intervention, that it seems custom-designed to make even decent drivers doubt their skills.
Fig. 2 Moving object detection results.
Figure 2a, c shows the results of moving object detection.
Figure 15 Example of multiple moving object detection.
Figure 4c shows the result of moving object detection.
Moving object detection plays a key role in video surveillance.
Background modeling and moving object detection are based on the adaptive background subtraction method.
The higher the F-measure, the better the accuracy of the moving object detection is.
The proposed technique deals with moving object detection and classification by utilizing consecutive frame subtraction.
(4 where A x,y) denotes the binarization result of moving object detection.
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