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A fast pedestrian detection via modified HOG feature

机译:通过改进的HOG功能快速进行行人检测

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摘要

The Histogram of Oriented Gradient (HOG) feature for pedestrian detection has achieved good results, but it is time-consuming. For resolving this problem, a modified method for HOG is proposed to reduce the dimension of the features. On the base of analyzing the process of HOG, nine independent HOG channels (HOG-C) are extracted according to the gradient orientation interval. Through evaluating the effectiveness of HOG-C for pedestrian detection individually, a combination of HOG channels (CHOG-C) feature is presented based on statistical regularities. Comprehensive experiments on INRIA database demonstrated the promising performance of the CHOG-C feature, and the experimental results shown that the dimension is reduced meanwhile without losing the accuracy.
机译:步行者直方图直方图(HOG)功能取得了不错的效果,但是很费时。为了解决该问题,提出了一种用于HOG的改进方法以减小特征的尺寸。在分析HOG过程的基础上,根据梯度取向间隔提取了9个独立的HOG通道(HOG-C)。通过分别评估HOG-C对行人检测的有效性,基于统计规律性提出了HOG通道(CHOG-C)功能的组合。在INRIA数据库上进行的综合实验证明了CHOG-C功能的良好前景,并且实验结果表明,该方法在减小尺寸的同时又不降低精度。

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