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Foveation: an alternative method to simultaneously preserve privacy and information in face images

机译:偏爱:同时保留面部图像中的隐私和信息的另一种方法

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This paper presents a real-time foveation technique proposed as an alternative method for image obfuscation while simultaneously preserving privacy in face deidentification. Relevance of the proposed technique is discussed through a comparative study of the most common distortions methods in face images and an assessment on performance and effectiveness of privacy protection. All the different techniques presented here are evaluated when they go through a face recognition software. Evaluating the data utility preservation was carried out under gender and facial expression classification. Results on quantifying the tradeoff between privacy protection and image information preservation at different obfuscation levels are presented. Comparative results using the facial expression subset of the FERET database show that the technique achieves a good tradeoff between privacy and awareness with 30% of recognition rate and a classification accuracy as high as 88% obtained from the common figures of merit using the privacy-awareness map. (C) 2017 SPIE and IS&T
机译:本文提出了一种实时聚焦技术,该技术可作为图像模糊处理的替代方法,同时在人脸识别中保留隐私。通过对人脸图像中最常见的失真方法的比较研究以及对隐私保护性能和有效性的评估,讨论了所提出技术的相关性。当本文介绍的所有不同技术通过面部识别软件时,都将得到评估。在性别和面部表情分类下评估数据实用程序的保存。给出了量化在不同混淆级别下隐私保护和图像信息保存之间权衡的结果。使用FERET数据库的面部表情子集进行的比较结果表明,该技术以30%的识别率和高达88%的分类准确度在隐私和意识之间取得了很好的权衡,使用隐私意识从普通绩效指标获得的分类准确度高达88%地图。 (C)2017 SPIE和IS&T

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