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Research of Moving Object Detection Algorithm Based on Non-Restraint Learning and Shadow Removal Algorithm

机译:基于非克制学习和阴影移除算法的移动物体检测算法研究

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A detection algorithm of moving objects which is robust and effective is proposed for the problem of the chaos and variety scenes. The background model based color quickly is build during the nonrestraint learning. According to the background of the chaos, it updates the model. However, shadow is also detected as moving object because of the same characters between them, so the algorithm of shadow removal based on its characteristic of chroma, lightness and crossover entropy was presented too. Finally, the algorithm was simulated in real-time and experimental effect, and achieved better results.
机译:提出了一种稳健且有效的移动物体的检测算法,用于混沌和各种场景。在非欣赏学习期间,基于背景模型的颜色很快就是构建的。根据混乱的背景,它更新模型。然而,由于它们之间的相同字符,阴影也被检测为移动物体,因此也提出了基于其色度,亮度和交叉熵的特性的阴影移除算法。最后,算法在实时和实验效果中模拟,取得了更好的结果。

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