通过基于相位的欧拉视频放大改进唇读的短语识别

Salam Nandakishor, D. Pati
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引用次数: 0

摘要

唇读是一种通过视觉观察嘴唇运动来理解言语的技巧。在说话的时候,我们嘴巴的细微运动或时间变化通常是肉眼看不见的。这主要是由于视觉感知的范围有限。这些难以察觉的视觉信息由有用的隐藏信息组成。利用欧拉视频放大(EVM)技术对视频进行放大,以揭示这些隐藏信息。本文采用基于相位的EVM方法,放大口腔运动的细微时空信息,用于短语识别任务。从三个正交平面(XY, XT和YT)中提取的局部二值模式直方图称为LBP-TOP作为视觉特征来表示嘴部运动。支持向量机(SVM)用于短语识别。实验在OuluVS数据库上进行。无EVM的唇读方法准确率为62%,而基于相位的EVM方法准确率为70%。结果表明,该方法对短语识别任务提取的视觉特征具有较强的鲁棒性和判别性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Phrase recognition using Improved Lip reading through Phase-Based Eulerian Video Magnification
Lip reading is a technique to understand speech by visual observations of the lip movements. While speaking the subtle motion or temporal variations of our mouth are generally invisible by naked humans eyes. It is mainly due to the limited range of visual perception. These imperceptible visual information consist of useful hidden information. The Eulerian video magnification (EVM) technique is used to magnify the video for revealing such hidden information. In this work, the phase based EVM method is used to magnify the subtle spatial and temporal information of the mouth movements for phrases recognition task. The local binary pattern histogram extracted from three orthogonal plane (XY, XT and YT), known as LBP-TOP is used as visual feature to represent mouth movements. The support vector machine (SVM) is used for recognition of phrases. The experiments are performed on OuluVS database. The lip-reading approach without EVM provides 62% accuracy whereas the phase based EVM method provides 70% accuracy. This shows that the proposed method extracts comparatively more robust and discriminative visual features for phrase recognition task.
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