Skip to main content
Log in

Panorama construction using binary trees

  • Original Paper
  • Published:
Signal, Image and Video Processing Aims and scope Submit manuscript

Abstract

We present a novel algorithm for computing a panorama from a video sequence, which is based on AVL binary trees and is called PCBT. The main characteristic of PCBT is to compute automatically the reference frame, which is used to project the rest of frames on a planar projection. We use the homography as the camera motion model, it is computed only frame to frame, and the rest of the homographies needed for compositing the panorama are automatically computed through the binary tree using the previously computed homographies. The experiments show that PCBT improves the results of Autopano Giga and Image Composite Editor, two well-known applications, and the results of Stitching_Detailed sample of the OpenCV library, for computing panoramas under a planar projection.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

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

    Article  MathSciNet  MATH  Google Scholar 

  2. Brown, M., Lowe, D.G.: Automatic panoramic image stitching using invariant features. Int. J. Comput. Vis. 74(1), 59–73 (2007)

    Article  Google Scholar 

  3. Silva, F.A., Hiraga, A.K., Artero, A.O., Paiva, M.S.V.: StitchingPHm—a new algorithm for panoramic images. Pattern Recognit. Image Anal. 24(1), 41–56 (2014)

    Article  Google Scholar 

  4. Kourogi, M., Kurata, T., Hoshino, J., Muraoka, Y.: Real-time image mosaicing from a video sequence. In: Proceedings of the 1999 International Conference on Image Processing, 1999. ICIP 99, vol. 4, pp. 133–137. IEEE (1999)

  5. Hsu, C.-T., Tsan, Y.-C.: Mosaics of video sequences with moving objects. Signal Process. Image Commun. 19(1), 81–98 (2004)

    Article  Google Scholar 

  6. Xia, M., Yao, M., Li, L., Lu, X.: Globally consistent alignment for mosaicking aerial images. In: 2015 IEEE International Conference on Image Processing (ICIP), pp. 3039–3043. IEEE (2015)

  7. Winkelman, F., Patras, I.: Online globally consistent mosaicing using an efficient representation. In: 2004 IEEE International Conference on Systems, Man and Cybernetics, vol. 4, pp. 3116–3121. IEEE (2004)

  8. Barhoumi, W., Bakkay, M.C., Zagrouba, E.: An online approach for multi-sprite generation based on camera parameters estimation. Signal Image Video Process. 7(5), 843–853 (2013)

    Article  Google Scholar 

  9. Hernandez-Lopez, F.J., Rivera, M.: Avscreen: a real-time video augmentation method. J. Real-Time Image Process. 10(2), 453–465 (2015)

    Article  Google Scholar 

  10. Shi, J., et al.: Good features to track. In: 1994 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1994. Proceedings of the CVPR’94, pp. 593–600. IEEE (1994)

  11. Lucas, B., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: Proceedings of the IJCAI, pp. 121–130 (1981)

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

    Article  Google Scholar 

  13. Baggio, D.L., Emami, S., Escriva, D.M., Ievgen, K., Mahmood, N., Saragih, J., Shilkrot, R.: Mastering OpenCV with Practical Computer Vision Projects. Packt Publishing, Limited, Birmingham (2012)

    Google Scholar 

  14. Hartley, A., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2006)

    MATH  Google Scholar 

  15. Adelson-Velskii, G.M., Landis, E.M.: An algorithm for the organization of information. Doklady Akademia Nauk SSSR 3, 1259–1263 (1962)

    MathSciNet  Google Scholar 

  16. Zeng, L., Zhang, S., Zhang, J., Zhang, Y.: Dynamic image mosaic via sift and dynamic programming. Mach. Vis. Appl. 25(5), 1271–1282 (2014)

    Article  Google Scholar 

  17. Hejazifar, H., Khotanlou, H.: Fast and robust seam estimation to seamless image stitching. Signal Image Video Process. 12(5), 885–893 (2018)

    Article  Google Scholar 

  18. Del Bimbo, A., Lisanti, G., Masi, I., Pernici, F.: Continuous recovery for real time pan tilt zoom localization and mapping. In: 2011 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS 2011), Klagenfurt, Austria, vol. 8 (2011)

  19. Colombari, A., Fusiello, A., Murino, V.: Segmentation and tracking of multiple video objects. Pattern Recognit. 40(4), 1307–1317 (2007)

    Article  MATH  Google Scholar 

  20. Brox, T., Malik, J.: Object segmentation by long term analysis of point trajectories. Comput. Vis. ECCV 2010, 282–295 (2010)

    Google Scholar 

  21. Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P., et al.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–612 (2004)

    Article  Google Scholar 

  22. Liao, T., Chen, J., Xu, Y.: Quality evaluation-based iterative seam estimation for image stitching. Signal Image Video Process (2019). https://doi.org/10.1007/s11760-019-01466-9

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Francisco J. Hernandez-Lopez.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hernandez-Lopez, F.J., Trejo-Sánchez, J.A. & Rivera, M. Panorama construction using binary trees. SIViP 14, 839–846 (2020). https://doi.org/10.1007/s11760-019-01616-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11760-019-01616-z

Keywords

Navigation