Local binary pattern based features for sign language recognition

被引：4
|
作者：
Hrúz M. [1 ]
Trojanová J. [1 ]
Železný M. [1 ]
机构：
[1] Faculty of Applied Sciences, University of West Bohemia, Pilsen
来源：
Pattern Recognition and Image Analysis | 2011年 / 21卷 / 3期
关键词：
Recognition Rate; Local Binary Pattern; Facial Landmark; Geometric Moment; Local Binary Pattern Feature;
D O I：
10.1134/S1054661811020416
中图分类号：
学科分类号：
摘要：
In this paper we focus on appearance features describing the manual component of Sign Language particularly the Local Binary Patterns. We compare the performance of these features with geometric moments describing the trajectory and shape of hands. Since the non-manual component is also very important for sign recognition we localize facial landmarks via Active Shape Model combined with Landmark detector that increases the robustness of model fitting. We test the recognition performance of individual features and their combinations on a database consisting of 11 signers and 23 signs with several repetitions. Local Binary Patterns outperform the geometric moments. When the features are combined we achieve a recognition rate up to 99. 75% for signer dependent tests and 57. 54% for signer independent tests. © 2011 Pleiades Publishing, Ltd.
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页码：398 / 401
页数：3
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