A Convolutional Neural Network for Nonrigid Structure from Motion. (28th April 2022)

• Record Type: Journal Article
• Authors: Wang, Yaming; Peng, Xiangyang; Huang, Wenqing; Wang, Meiliang
• Other Names: Mhamed Sayyouri Academic Editor.
• Is Part Of: International journal of digital multimedia broadcasting. Volume 2022(2022)
• Publication Date: 2022-04-28
• Subjects: Multimedia communications -- Periodicals; Digital audio broadcasting -- Periodicals; Mobile communication systems -- Periodicals; Digital audio broadcasting; Mobile communication systems; Multimedia communications; Periodicals; 621.382
• DOI: 10.1155/2022/3582037
• Languages: English
• ISSNs: 1687-7578

Abstract

Abstract : In this study, we propose a reconstruction and optimization neural network (RONN), a novel neural network for nonrigid structure from motion, which is completed by an unsupervised convolution neural network. Compared with the traditional method for directly solving 3D structures, our model focuses on depth information that is lost owing to projection. This mathematical model is developed using a convolutional neural network with three modules for integration, reconstruction, and optimization, as well as two prior-free loss functions. The proposed RONN achieves competitive accuracy on several tested sequences and high visual quality of various real video sequences.