Multi-classification Recognition Method Applied to Facial Image Based on Distribution Characteristic of Heavy-tailed Noise
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摘要: 针对传统人脸识别方法不能有效地适应重尾噪声下的人脸图像的拖尾情况,该文提出具有良好抗重尾噪声能力的t分布下的多分类人脸识别方法。该算法通过调整t分布中的自由度参数v,使t分布能够很好地适应添加重尾噪声后的人脸图像的多种拖尾情况,提高人脸识别效果。ORL和Yale数据集上的实验结果,验证了所提出的算法的可行性和有效性。
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关键词:
- 人脸识别 /
- 多元t分布 /
- 多元Gaussian分布 /
- 核方法 /
- 重尾噪声
Abstract: Multi-classification method under t distribution is proposed in order to solve the problem of the traditional face classification methods failing to settle tailing situation with heavy-tailed noise. By adjusting the degree of freedom parameter v, t distribution will adapt to a variety of tailing conditions better after heavy-tailed noise is added in facial images, at the same time, the recognition results will be improved. The experimental results on ORL and Yale show the feasibility and the effectiveness of the proposed algorithm.
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