Human detection using non-negative matrix factorization

Jing-Xiu Zeng, Chih-Yang Lin, Wei-Yang Lin
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Abstract

Currently, most of the human detection methods are based on low-level features. In this paper, we proposed a middle-level feature generation method based on non-negative matrix factorization (NMF) for human detection. We also proposed an improvement scheme to guarantee that a better middle-level feature can be achieved. The proposed scheme can be applied to a complex background and the experimental results are better than those when only the low-level feature is involved.
人类检测使用非负矩阵分解
目前,大多数人类检测方法都是基于底层特征。本文提出了一种基于非负矩阵分解(NMF)的中级特征生成方法。我们还提出了一个改进方案,以保证能够实现更好的中间层特性。该方法可以应用于复杂背景下,实验结果优于只考虑底层特征时的实验结果。
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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