Skip to main content
SpringerLink
Log in
Book cover

Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011 pp 463–472Cite as

Hand Held Mobile Video Stabilization Using Differential Motion Estimation

  • Conference paper

  • 2927 Accesses

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 131))

Abstract

The hand held mobile cameras suffer from different undesired slow motions during the scene capturing time. It is required to stabilize the video sequence by removing the undesired motion between the successive frames. Most of the existing methods are either very complex or does not perform well for slow and smooth motion of hand held mobile videos. In this paper a modified video stabilization algorithm for hand held camera videos is proposed which uses bicubic interpolation with Taylor series expansion to improve the estimation efficiency of the hierarchical differential global motion estimation. After motion estimation Gaussian kernel filtering is used to smoothen out estimated motion parameters. Then Inverse rotation smoothening is applied to remove the rotation effect from the stabilized transform chain. This reduces the accumulation error and minimizes missing image area significantly. The performance of the proposed algorithm is tested on various real time videos and also compared with existing algorithm.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   259.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Matsushita, Y., Ofek, E., Ge, W., Tang, X., Shum, H.Y.: Full frame video stabilization with motion inpainting. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(7), 1163–1178 (2006)

    Article  Google Scholar 

  2. Chang, H.C., Lai, S.H., Lu, K.R.: A robust and efficient video stabilization algorithm. In: ICME 2004, International Conference on Multimedia and Expo, June 2004, vol. 1, pp. 29–32 (2004)

    Google Scholar 

  3. Hu, R., Shi, R., Shen, I.F., Chen, W.: Video Stabilization Using Scale Invariant Features. In: 11th International Conference on Information Visualization (IV 2007). IEEE (2007)

    Google Scholar 

  4. Yang, J., Schonfeld, D., Mohamed, M.: Robust Video Stabilization based on particle filter racking of projected camera motion. IEEE Trans. on Circuits and Systems for Video Technology 19(7), 945–954 (2009)

    Article  Google Scholar 

  5. Pang, D., Chen, H., Halawa, S.: Efficient Video Stabilization with Dual-Tree Complex Wavelet Transform, EE368 Project Report, Spring (2010)

    Google Scholar 

  6. Szeliski, R.: Image Alignment and Stitching: A Tutorial. Technical Report MSR-TR, 2004-92, Microsoft Corp. (2004)

    Google Scholar 

  7. Farid, H., Woodward, J.B.: Video stabilization and Enhancement, TR 2007-605, Dartmouth College, Computer Science (1997)

    Google Scholar 

  8. Adda, O., Cottineau, N., Kadoura, M.: A Tool for Global Motion Estimation and Compensation for Video Processing. LEC/COEN 490, Concordia University, May 5 (2003)

    Google Scholar 

  9. Feng, L., Gleicher, M., Jin, H., Agarwala, A.: Content Preserving Warps for 3D Video Stabilization. In: Int. Conf. Proc. ACM SIGGRAPH 2009 papers, pp. 1–9. ACM, New York (2001)

    Google Scholar 

  10. Buehler, C., Bosse, M., Mcmillian, L.: Non-metric image based rendering for video stabilization. In: Proc. Computer Vision and Pattern Recognition, vol. 2, pp. 609–614 (2001)

    Google Scholar 

  11. Litvin, A., Konrad, J., Karl, W.: Probabilistic video stabilization using Kalman filtering and mosaicking. In: Proc. of IS&T/SPIE Symposium on Electronic Imaging, Image and Video Communications, vol. 1, pp. 663–674 (2003)

    Google Scholar 

  12. Jin, J.S., Zhu, Z., Xu, G.: Digital video sequence stabilization based on 2.5d motion estimation and inertial motion filtering. Real- Time Imaging 7(4), 357–365 (2001)

    Article  Google Scholar 

  13. Takacs, G., Chandrasekhar, V., Chen, D., Tsai, S., Grzeszczuk, R., Girod, B.: Unified real time tracking and recognition with rotation invariant fast features. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, San Fransisco, June 2010, vol. 1, pp. 217–222 (2010)

    Google Scholar 

  14. Pilu, M.: Video Stabilization as a Variational Problem and Numerical Solution with the Viterbi Method. In: Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 625–630 (2004)

    Google Scholar 

  15. Bergen, J.R., Anandan, P., Hanna, K.J., Hingorani, R.: Hierarchical Model based Motion Estimation. In: Proc. of Second European Conf. on Computer Vision, pp. 237–252 (1992)

    Chapter  Google Scholar 

  16. Anandan, P.: A Computational Framework and an Algorithm for the Measurement of Visual Motion. Int. Journal of Computer Vision 2(3), 283–310 (1989)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Deptt. of Electronics & Communication Engg., Truba I.E.I.T, Bhopal, India

    Paresh Rawat

  2. Deptt. of Electronics Engineering, MANIT, Bhopal, India

    Jyoti Singhai

Authors
  1. Paresh Rawat
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jyoti Singhai
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Paresh Rawat .

Editor information

Editors and Affiliations

  1. , Department of Mathematics, Indian Institute of Technology Roorkee, Uttarakhand, Roorkee, 247667, India

    Kusum Deep

  2. Department of Mathematics and, Computer Science, Liverpool Hope University, Hope Park, Liverpool, L16 9JD, United Kingdom

    Atulya Nagar

  3. , Department of Paper Technology, Indian Institute of Technology Roorkee, Uttarakhand, Roorkee, 247667, India

    Millie Pant

  4. Information Technology and Management, ABV-Indian Institute of, 109, E- Block, Gwalior, 474010, India

    Jagdish Chand Bansal

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer India Pvt. Ltd.

About this paper

Cite this paper

Rawat, P., Singhai, J. (2012). Hand Held Mobile Video Stabilization Using Differential Motion Estimation. In: Deep, K., Nagar, A., Pant, M., Bansal, J. (eds) Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011. Advances in Intelligent and Soft Computing, vol 131. Springer, New Delhi. https://doi.org/10.1007/978-81-322-0491-6_43

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-0491-6_43

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-0490-9

  • Online ISBN: 978-81-322-0491-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation