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데이터 증강을 통한 마스크 착용 얼굴 이미지에 강인한 얼굴 자세 추정
한경탁(Kyeongtak Han),홍성은(Sungeun Hong) 한국방송·미디어공학회 2022 방송공학회논문지 Vol.27 No.6
Due to the coronavirus pandemic, the wearing of a mask has been increasing worldwide; thus, the importance of image analysis on masked face images has become essential. Although head pose estimation can be applied to various face-related applications including driver attention, face frontalization, and gaze detection, few studies have been conducted to address the performance degradation caused by masked faces. This study proposes a new data augmentation that synthesizes the masked face, depending on the face image size and poses, which shows robust performance on BIWI benchmark dataset regardless of mask-wearing. Since the proposed scheme is not limited to the specific model, it can be utilized in various head pose estimation models.