Lipreading Using Spatiotemporal Histogram of Oriented Gradients

被引:0
作者
Palecek, Karel [1 ]
机构
[1] Tech Univ Liberec, Inst Informat Technol & Elect, Liberec, Czech Republic
来源
2016 24TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO) | 2016年
关键词
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We propose a visual speech parametrization based on histogram of oriented gradients (HOG) for the task of lipreading from frontal face videos. Inspired by the success of spatiotemporal local binary patterns, the features are designed to capture dynamic information contained in the input video sequence by combining HOG descriptors extracted from three orthogonal planes that span x, y and t axes. We integrate our features into a system based on hidden Markov model (HMM) and show that by utilizing robust and properly tuned parametrization this traditional scheme can outperform recent sophisticated embedding approaches to lipreading. We perform experiments on three different datasets, two of which are publicly available. In order to conduct an unbiased feature comparison, the process of model learning including hyperparameter tuning is as automatized as possible. To this end, we rely heavily on cross validation.
引用
收藏
页码:1882 / 1885
页数:4
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