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Multi-Stage Feature Pyramid Stereo Network-Based Disparity Estimation Approach for Two to Three-Dimensional Video Conversion
Pan B.1; Zhang L.1; Wang H.2
2020-08-04
Source PublicationIEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
ISSN1051-8215
Volume31Issue:5Pages:1862-1875
Abstract

Disparity estimation is a popular topic in computer vision and has drawn increasing attention in recent years. In this article, we propose a new multi-stage network for the purpose of two to three-dimensional video conversion that contains two training stages: An initial disparity estimation as the first training stage and depth-image-based rendering (DIBR) as an extra component to form the second training stage. In the first training stage, we propose a revised end-to-end feature pyramid stereo network, in which the original non-pyramid structure is replaced by a bottom-up convolutional neural network pyramid for disparity regression. It utilizes the spatial information by concatenating different scale features to boost the performance on boundary consistency. Mirror connections between feature extraction and disparity regression on the corresponding layers are also added to improve the quality of the results. In the second stage, we propose an improved disocclusion filling technique in the DIBR branch and connect the non-neural-network method to the disparity estimation network. This two-stage training strategy can work effectively to generate the improved disparity estimation for two to three-dimensional video conversion. Extensive experiments are conducted and some selected state-of-the-art algorithms are compared with our proposed approach on the popular KITTI2015 and Scene Flow datasets. The results demonstrate that our estimated disparity map can generate high quality 3D images.

Keyword2d To 3d Video Conversion Deep Learning Depth Image Based Rendering (Dibr) Disparity Estimation Feature Pyramid Neural Network
DOI10.1109/TCSVT.2020.3014053
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000647394100015
PublisherIEEE
Scopus ID2-s2.0-85099568038
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Citation statistics
Document TypeJournal article
CollectionFaculty of Science and Technology
Corresponding AuthorZhang L.
Affiliation1.Faculty of Science and Technology, University of Macau, Taipa, Macao
2.School of Informatics, Xiamen University, Xiamen, 361005, China
First Author AffilicationFaculty of Science and Technology
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Pan B.,Zhang L.,Wang H.. Multi-Stage Feature Pyramid Stereo Network-Based Disparity Estimation Approach for Two to Three-Dimensional Video Conversion[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2020, 31(5), 1862-1875.
APA Pan B.., Zhang L.., & Wang H. (2020). Multi-Stage Feature Pyramid Stereo Network-Based Disparity Estimation Approach for Two to Three-Dimensional Video Conversion. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 31(5), 1862-1875.
MLA Pan B.,et al."Multi-Stage Feature Pyramid Stereo Network-Based Disparity Estimation Approach for Two to Three-Dimensional Video Conversion".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 31.5(2020):1862-1875.
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