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CCoLBP: Chromatic Co-Occurrence of Local Binary Pattern for Face Presentation Attack Detection

机译:CCoLBP:用于面部表情攻击检测的本地二进制模式的色共现

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To counter face presentation attack in face recognition system, the chromatic facial texture differences between the real faces and the facial artefacts are fully analyzed, and chromatic co-occurrence of local binary pattern (CCoLBP) is proposed to investigate the inter-channel based information. Based on the principle of presentation attack and its influence on color component of the face image, a face presentation attack detection (PAD) scheme based on CCoLBP is proposed. By combining intra-channel based facial texture and CCoLBP feature, the differences of color distortion and texture distribution between the real faces and the artefacts are characterized. With these features, the detection is accomplished by using a Softmax classifier. Experiments are done with 5 public databases, and the experimental results and analysis indicate the effectiveness of CCoLBP, and it can achieve good performance in cross-database testing. It has great potential in the application of face PAD with real-time requirement.
机译:为了对抗人脸识别系统中的人脸呈现攻击,充分分析了真实人脸与人脸伪影之间的彩色人脸纹理差异,并提出了基于局部二值模式(CCoLBP)的彩色共现来研究基于通道间的信息。基于表现攻击的原理及其对人脸图像色彩成分的影响,提出了一种基于CCoLBP的人脸表现攻击检测(PAD)方案。通过结合基于通道内的面部纹理和CCoLBP特征,可以表征真实面部和伪像之间的颜色失真和纹理分布差异。通过这些功能,可以通过使用Softmax分类器完成检测。通过5个公共数据库进行了实验,实验结果和分析表明CCoLBP是有效的,并且可以在跨数据库测试中取得良好的性能。在具有实时需求的人脸PAD的应用中具有很大的潜力。

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