A new algorithm for the detection of deepfakes in digital videos is presented. The I-frames were extracted in order to provide faster computation and analysis than approaches described in the literature. To identify the discriminating regions within individual video frames, the entire frame, background, face, eyes, nose, mouth, and face frame were analyzed separately. From the Discrete Cosine Transform (DCT), the Beta components were extracted from the AC coefficients and used as input to standard classifiers. Experimental results show that the eye and mouth regions are those most discriminative and able to determine the nature of the video under analysis.

翻译：提出了一种用于数字视频中深度伪造检测的新算法。为提供比文献中所述方法更快的计算和分析速度，本文提取了I帧。为识别单个视频帧内的判别区域，分别对整个帧、背景、人脸、眼睛、鼻子、嘴巴及人脸框进行了分析。通过离散余弦变换，从交流系数中提取Beta分量，并将其作为标准分类器的输入。实验结果表明，眼睛和嘴巴区域是最具判别性的区域，能够确定待分析视频的真实性。