Human Detection Using HOG-SVM, Mixture of Gaussian and Background Contours Subtraction

Abdourahman Houssein Ahmed, K. Kpalma, Abdoulkader Osman Guédi
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引用次数: 15

Abstract

Automatic moving object/Human detection in a video sequence is one of the most difficult problems in the field of image processing and computer vision. The HOG-SVM provides a detection windows that is not perfectly adjusted to the silhouette of the Human detected. It is possible to apply a postprocess based on background subtraction to improve the segmentation of the detection. In this paper, we present thus a detection method that improves results provided by HOG-SVM with a combination of mixture of Gaussian and background contours subtraction.
基于HOG-SVM、混合高斯和背景轮廓相减的人体检测
视频序列中运动物体/人的自动检测是图像处理和计算机视觉领域的难题之一。HOG-SVM提供了一个不完全适应被检测人轮廓的检测窗口。可以应用基于背景减法的后处理来改进检测的分割。因此,在本文中,我们提出了一种改进HOG-SVM的检测方法,该方法结合了高斯和背景轮廓相减的混合方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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