基于周期性运动检测的手势识别

Masahito Takahashi, K. Irie, Kenji Terabayashi, K. Umeda
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引用次数: 9

摘要

本文提出了一种从图像中识别周期性手势的方法。该方法利用快速傅里叶变换(FFT)对时间序列强度图像进行振幅谱和相位谱分析。将FFT应用于低分辨率图像的每个像素。该方法包括两个步骤。首先,从振幅谱中检测出p个周期运动区域。其次,该方法利用检测到的周期运动区域的相位谱对手势进行分类;该方法不依赖于颜色信息,对光照条件和肤色个体差异具有较强的鲁棒性。通过实验验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Gesture recognition based on the detection of periodic motion
In this paper, we propose a method to recognize periodic gestures from images. The proposed method uses a amplitude spectrum and a phase spectrum that are obtained by applying Fast Fourier Transform (FFT) to a time series of intensity images. FFT is applied to each pixel of low-resolution images. The method consists of 2 steps. First, the method detects p eriodic motion regions from the amplitude spectrum. Secondly, the method uses the phase spectrum in the detected periodic motion region to classify the gestures. The proposed method is robust to lighting conditions and individual differences in skin color because it does not rely on color information. Several experiments are performed to demonstrate the effectiveness of the proposed method.
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