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The role of prior in image based 3D modeling: a survey

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Abstract

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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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61371166, and 61422107) and the Natural Science Foundation of Jiangsu Province, China (BK20130583).

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  1. Lab for Computational Imaging Technology and Engineering, School of Electronic Science and Engineering, Nanjing University, Nanjing, 210023, China

    Hao Zhu, Yongming Nie, Tao Yue & Xun Cao

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  1. Hao Zhu
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Correspondence to Xun Cao.

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Hao Zhu received the BS degree from Department of Electronic Science and Technology, Nanjing University (NJU), China in 2013. He is currently working toward the PhD degree of electronic science and technology at NJU. His interests include computer vision and computational imaging.

Yongming Nie received the BS degree from Department of Mathematics, Tianshui Normal University, China in 2009, and MS degree from the Department of Mathematics, Nanchang University, China in 2012. He is currently working toward the PhD degree of electronic science and technology in Nanjing University. His research interests mainly include computer vision and machine learning.

Tao Yue received the BS degree in automation from Northwestern Polytechnical University, China in 2009, and the PhD degree from Tsinghua University, China in 2015. He is currently an associate researcher with the School of Electronic Science and Engineering, Nanjing University, China. His research interests mainly include image processing and computational photography.

Xun Cao received his BS degree from Nanjing University (NJU), China in 2006, and PhD degree from the Department of Automation, Tsinghua University, China in 2012. He is currently a professor at the School of Electronic Science and Engineering, NJU. Dr. Cao was visiting Philips Research, Aachen, Germany during 2008, and Microsoft Research Asia, China during 2009 and 2010. He was a visiting scholar at the University of Texas at Austin, USA from 2010 to 2011. His research interests include computational photography, image based modeling and rendering, and 3D TV systems. He is the awardee of the NSFC Excellent Young Scholars Program in 2014.

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Zhu, H., Nie, Y., Yue, T. et al. The role of prior in image based 3D modeling: a survey. Front. Comput. Sci. 11, 175–191 (2017). https://doi.org/10.1007/s11704-016-5520-8

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