Abstract
In this paper, a novel 3D reconstruction with multi-view texture mapping method based on Kinect 2 is proposed. Camera poses of all chosen key frames are optimized according to photometric consistency. Optimized camera poses can make the projected point from vertices to different views get closer. A small range of translations with limited calculation is added in this method. A new form of data term and smoothness term in Markov Random Field (MRF) objective function is presented. The outlier images are rejected before view selection and Poisson blending are applied in the end. Experimental results show that our method achieves a high-quality 3D model with high fidelity texture.
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References
Newcombe, R.A., et al.: KinectFusion: real-time dense surface mapping and tracking. In: 2011 10th IEEE International Symposium on Mixed and Augmented Reality, Basel, pp. 127–136 (2011). doi:10.1109/ISMAR.2011.6092378
Liu, S., Li, W., Ogunbona, P., Chow, Y.W.: Creating simplified 3D models with high quality textures. In: 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA), Adelaide, SA, pp. 1–8 (2015). doi:10.1109/DICTA.2015.7371249
Zhou, Q.Y., Koltun, V.: Color map optimization for 3D reconstruction with consumer depth cameras. ACM Trans. Graph. 33(4), 1–10 (2014)
Jeon, J., Jung, Y., Kim, H., Lee, S.: Texture map generation for 3D reconstructed scenes. Vis. Comput. 32(6), 955–965 (2016)
Wang, L., Kang, S.B., Szeliski, R., Shum, H.Y.: Optimal texture map reconstruction from multiple views. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, vol. 1, pp. I-347–I-354 (2001)
Lempitsky, V., Ivanov, D.: Seamless mosaicing of image-based texture maps. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–6 (2007)
Gal, R., Wexler, Y., Ofek, E., Hoppe, H., Cohen-Or, D.: Seamless montage for texturing models. Comput. Graph. Forum 29, 479–486 (2010)
Crete, F., Dolmiere, T., Ladret, P., Nicolas, M.: The blur effect: perception and estimation with a new no-reference perceptual blur metric. In: Electronic Imaging, pp. 64920I–64920I-11 (2007)
Kerl, C., Sturm, J., Cremers, D.: Robust odometry estimation for RGB-D cameras. In: 2013 IEEE International Conference on Robotics and Automation, Karlsruhe, pp. 3748–3754 (2013)
Waechter, M., Moehrle, N., Goesele, M.: Let there be color! Large-scale texturing of 3d reconstructions. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8693, pp. 836–850. Springer, Cham (2014). doi:10.1007/978-3-319-10602-1_54
Rez, P., Gangnet, M., Blake, A.: Poisson image editing. ACM Trans. Graph. 22(3), 313–318 (2003)
Acknowledgments
This work is supported in part by the National Natural Science Foundation of China (Grant No. 61401390).
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Ye, X., Wang, L., Li, D., Zhang, M. (2017). 3D Reconstruction with Multi-view Texture Mapping. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10636. Springer, Cham. https://doi.org/10.1007/978-3-319-70090-8_21
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DOI: https://doi.org/10.1007/978-3-319-70090-8_21
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