An Object Recognition Method Using RGB-D Sensor

Daisuke Maeda, M. Morimoto
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引用次数: 1

Abstract

To recognize objects within narrow categories, it is important to extract effective features from small number of training samples. In this paper, first we discuss several depth features to improve object recognition accuracy. After that, we also discuss feature dimension reduction when we have insufficient training samples.
基于RGB-D传感器的物体识别方法
为了在狭窄的分类中识别目标,从少量的训练样本中提取有效的特征是很重要的。本文首先讨论了提高目标识别精度的几种深度特征。之后,我们还讨论了训练样本不足时的特征降维问题。
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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