Multinomial Naive Bayes for real-time gender recognition

被引：0

作者：

Vergara, Diego ^{[1
]}

Hernandez, Sergio ^{[1
]}

Jorquera, Felipe ^{[1
]}

机构：

[1] Univ Catolica Maule, Geospatial Lab, Talca, Chile

来源：

2016 XXI SYMPOSIUM ON SIGNAL PROCESSING, IMAGES AND ARTIFICIAL VISION (STSIVA) | 2016年

关键词：

FACE; CLASSIFICATION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Existing implementations of face recognition systems are created under controlled environments and tested using a limited amount of data. Also, these techniques have a high computational cost which forbids incremental learning that is required in real-time. We propose a gender estimation implementation based on Multinomial Naive Bayes and Local Binary Patterns. The method is tested in a modern age and gender recognition dataset with realistic examples. In order to get state-of-the-art results, Adaboost is also proposed and tested.

引用

页数：6

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