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According to formula (6), the multi-objective optimization model of moving objects is obtained.
Finally, the multi-objective optimization algorithm of moving objects is proposed by using the crowd model to predict the status and the position of the target.
Then, the multi-objective optimization algorithm of moving objects is proposed by using the crowd model to predict the status and the position of the target.
The ability to detect moving objects is an ethologically salient function.
A simple, fast and accurate light line technique for direct detection of 3D shape of moving objects is presented.
Tracking moving objects is one of the most important but problematic features of motion analysis and understanding.
Similar(29)
But these moving people or moving objects are difficult to be modeled in simulations.
Moving objects are classified into three categories: pedestrians, cyclists, and motor vehicles.
Photographs of moving objects are almost always a little blurry — or a lot blurry, if the objects are moving rapidly enough.
Moreover, all frames have the same handshake or object motion blur, and moving objects are in the same position in all frames.
Moving objects are another common problem.
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