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Benchmark face detection using a face recognition database

机译:使用面部识别数据库进行基准面检测

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A framework is proposed to generate datasets good for benchmarking face detection using database meant for benchmarking face recognition. Instead of the common way of collecting images manually, the datasets from the proposed framework are made by a synthesis process with two phases: intrinsic parameterization and extrinsic parameterization. The former parameterizes the intrinsic variables that affect the appearance of a face, while the latter parameterizes the extrinsic variables that dominate how faces appear on background images as required by a test criterion. Experiments reveal that the proposed framework can generate test samples similar to those available from a popular face detection database, and also samples unavailable from existing face databases.
机译:建议使用用于基准测试人脸识别的数据库生成用于基准测试面部检测的基准测试的数据集。代替手动收集图像的常用方式,所提出的框架的数据集由具有两个阶段的合成过程进行:内在参数化和外部参数化。前者参数化影响面部外观的内部变量,而后者参数化了根据测试标准所要求的主导地位面部的外在变量。实验表明,所提出的框架可以生成类似于流行面部检测数据库可用的测试样本,并且还可以从现有面部数据库中使用的样本。

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