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Feature Points Selection for Rectangle Panorama Stitching

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Proceedings of ELM 2018 (ELM 2018)

Part of the book series: Proceedings in Adaptation, Learning and Optimization ((PALO,volume 11))

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Abstract

Panoramic images can provide users with large view scene, which is widely used in various fields. Image stitching can combine images of adjacent views with small horizon field into a single image with large horizon. Currently stitching method can provide a rectangle panorama by cropped method to view or print. However, this method can occur shape distortion, and information loss. In this paper, we propose a novel feature points selection method to generate rectangle panorama image. First, to avoid local distortion in overlap** region, matched feature points are selected by feature cluster analysis. And then, depending on selected feature points, we establish mesh war** method to produce rectangle mesh. At last, bilinear interpolation algorithm is used to obtain the rectangle panorama image. Experimental results show that the proposed method can effectively stitch different view image to generate rectangle panorama without shape distortion.

This work was supported by Shandong Province Natural Science Foundation under Grants ZR2017QF006, ZR2016FB20, National Natural Science Foundation of China under Grants 61801414, 61703360, 61572418, 61601261.

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References

  1. Szeliski, R.: Image alignment and stitching: a tutorial landsat. Found. Trends Comput. Graph. Vis. 2(1), 1–104 (2006)

    Article  MathSciNet  Google Scholar 

  2. Zelnik-Manor, L., Peters, G., Perona, P.: Squaring the circle in panoramas. In: Proceedings of ICCV, pp. 1292–1299 (2005)

    Google Scholar 

  3. Lin, W.Y., Liu, S., Mastsushita, Y., et al.: Smoothly varying affine stitching. In: Proceedings of CVPR, pp. 345–352 (2011)

    Google Scholar 

  4. Zaragoza, J., Chin, T.J., Tran, Q.H.: As-projective-as-possible image stitching with moving DLT. IEEE Trans. Pattern Anal. Mach. Intell. 36(7), 1285–1298 (2014)

    Article  Google Scholar 

  5. Goferman, S., Zelnik-Manor, L., Tal, A.: Context-aware saliency detection. IEEE Trans. Pattern Anal. Mach. Intell. 34(10), 1915–1926 (2012)

    Article  Google Scholar 

  6. Zhang, F., Liu, F.: Parallax-tolerant image stitching. In: Proceedings of CVPR, pp. 3262–3269 (2014)

    Google Scholar 

  7. Chang, C.H., Sato, Y., Chuang, Y.Y.: Shape-preserving half-projective warps for image stitching. In: Proceedings of CVPR, pp. 3254–3261 (2014)

    Google Scholar 

  8. Chai, Q., Liu, S.: Shape-optimizing hybrid war** for image stitching. In: Proceedings of ICIP, pp. 1–6 (2016)

    Google Scholar 

  9. Lin, C., Pankanti, S., Ramamurthy, K.N., Aravkin, A.Y.: Adaptive as-natural-as-possible image stitching. In: Proceedings of CVPR, pp. 1155–1163 (2015)

    Google Scholar 

  10. Lu, Y., Hua, Z.Z., Gao, K., Xu, T.F.: Multi-perspective image stitching and regularization via hybrid structure war**. Comput. Sci. Eng. 20(2), 10–23 (2018)

    Article  Google Scholar 

  11. Chen, Y.S., Chuang, Y.Y.: Natural image stitching with global similarity prior. In: Proceedings of ECCV, pp. 186–201 (2016)

    Google Scholar 

  12. ** with global similarity constraint. Computer Vision and Pattern Recognition, ar**v:1702.07935 (2017)

  13. Barnes, C., Shechtman, E., Finkelstein, A., Goldman, D.B.: PatchMatch: a randomized correspondence algorithm for structural image editing. ACM Trans. Graph. 28(3), 1–8 (2012)

    Article  Google Scholar 

  14. Kopf, J., Kienzle, W., Drucker, S., Kang, S.B.: Quality prediction for image completion. ACM Trans. Graph. 31(6), 1–8 (2012)

    Google Scholar 

  15. He, K., Chang, H., Sun, J.: Rectangling panoramic images via war**. ACM Trans. Graph. 32(4), 1–9 (2013)

    MATH  Google Scholar 

  16. Avidan, S., Shamir, A.: Seam carving for content-aware image resizing. ACM Trans. Graph. 26(3), 1–10 (2007)

    Article  Google Scholar 

  17. Yan, W.Q., Hou, C.P.: Reducing perspective distortion for stereoscopic image stitching. In: Proceedings of IEEE ICME Workshop, pp. 1–6 (2016)

    Google Scholar 

  18. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis 60(2), 91–110 (2004)

    Article  Google Scholar 

  19. He, Q., **, X., Du, C., Zhuang, F., Shi, Z.: Clustering in extreme learning machine feature space. Neurocomputing 128, 88–95 (2014)

    Article  Google Scholar 

  20. Heckbert, P.S.: Fundamentals of texture map** and image war**. M.S. thesis, Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA, USA (1989)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computer and Control Engineering, Yantai University, Yantai, China

    Weiqing Yan, **dong Xu & **angrong Tong

  2. Yantai Mind PointEye Intelligent Technology Co., Ltd., Yantai, China

    Shuigen Wang

  3. School of Electrical and Information Engineering, Tian** University, Tian**, China

    Guanghui Yue

  4. School of Software, Qufu Normal University, **ing, China

    Laihua Wang

Authors
  1. Weiqing Yan
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  2. Shuigen Wang
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  3. Guanghui Yue
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  4. **dong Xu
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  5. **angrong Tong
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  6. Laihua Wang
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Corresponding author

Correspondence to Weiqing Yan .

Editor information

Editors and Affiliations

  1. Institute of Information and Control, Hangzhou Dianzi University, **asha, Hangzhou, China

    Jiuwen Cao

  2. Department of Computer and Information Science, University of Macau, Taipa, Macao

    Chi Man Vong

  3. Nokia Bell Labs, Cybersecurity Research, Espoo, Finland

    Yoan Miche

  4. Department of Information and Logistics Technology, University of Houston, Houston, TX, USA

    Amaury Lendasse

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Yan, W., Wang, S., Yue, G., Xu, J., Tong, X., Wang, L. (2020). Feature Points Selection for Rectangle Panorama Stitching. In: Cao, J., Vong, C., Miche, Y., Lendasse, A. (eds) Proceedings of ELM 2018. ELM 2018. Proceedings in Adaptation, Learning and Optimization, vol 11. Springer, Cham. https://doi.org/10.1007/978-3-030-23307-5_13

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