The Visual Computer

, Volume 29, Issue 4, pp 253–263 | Cite as

Cylindrical panoramic mosaicing from a pipeline video through MRF based optimization

  • Chuan Niu
  • Fan Zhong
  • Songhua Xu
  • Chenglei Yang
  • Xueying Qin
Original Article


Stratum structure detection is a fundamental problem in geological engineering. One of the most commonly employed detection technologies is to shoot videos of a borehole using a forward moving camera. Using this technology, the problem of stratum structure detection is transformed into the problem of constructing a panoramic image from a low quality video. In this paper, we propose a novel method for creating a panoramic image of a borehole from a video sequence without the need of camera calibration and tracking. To stitch together pixels of neighboring image frames, our camera model is designed with a focal length changing feature, along with a small rotational freedom in the two-dimensional image space. Our camera model assumes that target objects lie on a cylindrical wall and that the camera moves forward along the central axis of the cylindrical wall. Based on these two assumptions, our method robustly resolves these two degrees-of-freedoms in our camera model through KLT feature tracking. Since the quality of the result video is affected by possible illumination overflow, camera lens blurring, and low video resolution, we introduce a cost function for eliminating seams between stitching strips. Our cost function is designed based on Markov Random Field and optimized using a belief propagation algorithm. Using our method, we can automatically construct a panorama image with good resolution, smoothness, and continuousness both in the texture and illumination space. Experiment results show that our method could efficiently generate panoramas for long video sequences with satisfying visual quality.


Panorama MRF optimization Forward moving camera Belief propagation algorithm 



This work is supported by the National Natural Science Foundation of China (Nos. U1035004, 61003149, 61272243, 61173070), Shandong Province Natural Science Foundation (Nos. ZR2010FQ011, ZR2012FQ026), and the Natural Science Fund for Distinguished Young Scholars of Shandong Province (No. JQ200920). Songhua Xu performed this research as a Eugene P. Wigner Fellow and staff member at the Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy under Contract DE-AC05-00OR22725.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.School of Computer Science and TechnologyShandong UniversityJinanP.R. China
  2. 2.Shandong Provincial Key Laboratory of Software EngineeringJinanP.R. China
  3. 3.Oak Ridge National LaboratoryOak RidgeUSA

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