PDF(Pubmed)
Abstract：
The panoramic stereo video has brought a new visual experience for the audience with its immersion and stereo effect. In panoramic stereo video, the face is an important element. However, the face image in panoramic stereo video has varying degrees of deformation. This brings new challenges to face recognition. Therefore, this paper proposes a face recognition model DCM2Net (Deformable Convolution MobileFaceNet) for panoramic stereo video. The model mainly integrates the feature information between channels during feature fusion, redistributes the information between channels in the deeper part of the network, and fully uses the information between different channels for feature extraction. This paper also built a panoramic stereo video live system, using the DCM2Net model to recognize the face in panoramic stereo video, and the recognition results are displayed in the video. After experiments on different datasets, the results show that our model has better results on popular datasets and panoramic datasets.
摘要：
全景立体视频以其沉浸和立体效果为观众带来了全新的视觉体验。在全景立体视频中，脸是一个重要的元素。然而,全景立体视频中的人脸图像有不同程度的变形。这给人脸识别带来了新的挑战。因此,提出了一种适用于全景立体视频的人脸识别模型DCM2Net(DeformableConvolutionMobileFaceNet)。该模型在特征融合过程中主要对通道间的特征信息进行融合,在网络深处的信道之间重新分配信息，并充分利用不同通道之间的信息进行特征提取。本文还搭建了全景立体视频直播系统,使用DCM2Net模型识别全景立体视频中的人脸，识别结果显示在视频中。在不同的数据集上进行实验后，结果表明，我们的模型在流行数据集和全景数据集上都有更好的结果。
