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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
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)
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)
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)
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)
Pang, D., Chen, H., Halawa, S.: Efficient Video Stabilization with Dual-Tree Complex Wavelet Transform, EE368 Project Report, Spring (2010)
Szeliski, R.: Image Alignment and Stitching: A Tutorial. Technical Report MSR-TR, 2004-92, Microsoft Corp. (2004)
Farid, H., Woodward, J.B.: Video stabilization and Enhancement, TR 2007-605, Dartmouth College, Computer Science (1997)
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)
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)
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)
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)
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)
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)
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)
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)
Anandan, P.: A Computational Framework and an Algorithm for the Measurement of Visual Motion. Int. Journal of Computer Vision 2(3), 283–310 (1989)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights 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)