3D Reconstruction with Multi-view Texture Mapping

  • Xiaodan Ye
  • Lianghao Wang
  • Dongxiao Li
  • Ming Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10636)


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.


Camera poses optimization Markov Random Field (MRF) Texture mapping 



This work is supported in part by the National Natural Science Foundation of China (Grant No. 61401390).


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.College of Information Science and Electronic EngineeringZhejiang UniversityHangzhouChina
  2. 2.Zhejiang Provincial Key Laboratory of Information Processing, Communication and NetworkingHangzhouChina
  3. 3.State Key Lab for Novel Software TechnologyNanjing UniversityNanjingChina

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