期刊
FRONTIERS OF COMPUTER SCIENCE
卷 11, 期 2, 页码 175-191出版社
HIGHER EDUCATION PRESS
DOI: 10.1007/s11704-016-5520-8
关键词
prior information; consistency-based stereo; smoothness; illumination; silhouette; specific prior
类别
资金
- National Natural Science Foundation of China [61371166, 61422107]
- Natural Science Foundation of Jiangsu Province, China [BK20130583]
The prior knowledge is the significant supplement to image-based 3D modeling algorithms for refining the fragile consistency-based stereo. In this paper, we review the image-based 3D modeling problem according to prior categories, i.e., classical priors and specific priors. The classical priors including smoothness, silhouette and illumination are well studied for improving the accuracy and robustness of the 3D reconstruction. In recent years, various specific priors which take advantage of Manhattan rule, geometry template and trained category features have been proposed to enhance the modeling performance. The advantages and limitations of both kinds of priors are discussed and evaluated in the paper. Finally, we discuss the trend and challenges of the prior studies in the future.
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