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Multiple human detection in images based on differential evolution and HOG-LBP

机译:基于差分演化和猪LBP的图像中的多人检测

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In this paper a method for multiple human detection in the image has been presented. This method uses differential evolution (DE) algorithm to improve window position detection speed and HOG-LBP algorithm for feature extraction. Fitness function for DE algorithm is SVM and in the final state, a postprocessing on detected windows by DE algorithm is performed. This method has been tested on INRIA datasets and its precision for detecting humans in the image is 92% which is better than state of the art methods.
机译:在本文中,已经介绍了一种用于图像中的多种人类检测​​的方法。该方法使用差分演进(DE)算法来改善特征提取的窗口位置检测速度和HOG-LBP算法。 DE算法的健身功能是SVM,并且在最终状态下,执行DE算法对检测到的窗口的后处理。该方法已经在Inria数据集上进行了测试,并且其用于检测图像中的人类的精度为92%,这比现有技术的状态更好。

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