Abstract
Jitter or unintentional motion during image capture, poses a critical problem for any image processing application. Video stabilization is a technique used to correct images against unintentional camera motion. We propose a simple and fast video stabilization algorithm that can be used for real time pre-processing of images, which is especially useful in automotive vision applications. Corner and edge based features have been used for the proposed stabilization method. An affine model is used to estimate the motion parameters using these features. A scheme to validate the features and a variant of iterative least squares algorithm to eliminate the outliers is also proposed. The motion parameters obtained are smoothed using a moving average filter, which eliminates the higher frequency jitters obtained due to unintentional motion. The algorithm can be used to correct translational and rotational distortions arising in the video due to jitter.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Vella, F., Castorina, A., Mancuso, M., Messina, G.: Digital image stabilization by adaptive block motion vector filtering. IEEE Trans. on Consumer Electronics 48(3) (August 2002)
Lowe, D.: Distinctive image features from scale-invariant key points. International Journal of Computer Vision 60(2), 91–110 (2004)
Fischler, M.A., Bolles, R.C.: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Comm. of the ACM 24, 381–395 (1981)
Jin, J.S., Zhu, Z., Xu, G.: A Stable Vision System for Moving Vehicles. IEEE Transaction on Intelligent Transportation Systems 1(1), 32–39 (2000)
Ko, S.J., Lee, S.H., Lee, K.H.: Digital image stabilizing algorithms based on bit-plane matching. IEEE Transaction on Consumer Electronics 44(3), 617–622 (1998)
Litvin, A., Konrad, J., Karl, W.C.: Probabilistic video stabilization using Kalman filtering and mosaicking. In: Proc. of SPIE Electronic Imaging, vol. 5022, pp. 663–674 (2003)
Chang, J., Hu, W., Cheng, M., Chang, B.: Digital image translational and rotational motion stabilization using optical flow technique. IEEE Transactions on Consumer Electronics 48(1), 108–115 (2002)
Harris, C., Stephens, M.: A combined corner and edge detection. In: Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 287–293 (May 2002)
Tico, M., Vehvilainen, M.: Robust Method of Videos Stabilization. In: EUSIPCO (September 2007)
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., vol. 1, pp. 29–32, 7, 30, 40, 49, 64. IEEE, Los Alamitos (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kancharla, T., Gindi, S. (2011). A Real Time Video Stabilization Algorithm. In: Abraham, A., Mauri, J.L., Buford, J.F., Suzuki, J., Thampi, S.M. (eds) Advances in Computing and Communications. ACC 2011. Communications in Computer and Information Science, vol 193. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22726-4_37
Download citation
DOI: https://doi.org/10.1007/978-3-642-22726-4_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22725-7
Online ISBN: 978-3-642-22726-4
eBook Packages: Computer ScienceComputer Science (R0)