Abstract
Video stabilization methods cannot compensate entire unwanted motions of an unstable video. In this paper, we present a new performance metric which can effectively measure the stability of a video. Our hypothesis is that in case of non dynamic background, the background motion is zero without the foregrounds of a stable video when a video taken by a fixed camera. Firstly, the foregrounds of a stabilized video are discarded, then, each background pixel motion is determined between the two consecutive background frames in two directions separately, afterwards, an average motion of each pixel is computed. These mean motions determine the stability of a video. The more unstable video will have more background motions. The background motion is a criterion to evaluate the stability of a video. The experimental results prove the efficacy of our proposed approach.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Mean Displacement Error.
- 2.
Average Mean Displacement Error.
References
Zhang, C., Chockalingam, P., Kumar, A., Burt, P., Lakshmikumar, A.: Qualitative assessment of video stabilization and mosaicking systems. In: IEEE Workshop on Applications of Computer Vision WACV 2008, pp. 1–6. IEEE (2008)
Baker, S., Bennett, E., Kang, S.B., Szeliski, R.: Removing rolling shutter wobble. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2392–2399. IEEE (2010)
Liu, S., Wang, Y., Yuan, L., Bu, J., Tan, P., Sun, J.: Video stabilization with a depth camera. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 89–95. IEEE (2012)
Liu, S., Yuan, L., Tan, P., Sun, J.: Bundled camera paths for video stabilization. ACM Trans. Graph. (TOG) 32(4), 78 (2013)
Kopf, J.: 360 video stabilization. ACM Trans. Graph. (TOG) 35(6), 195 (2016)
Liu, F., Gleicher, M., Jin, H., Agarwala, A.: Content-preserving warps for 3D video stabilization. In: ACM Transactions on Graphics (TOG), vol. 28, p. 44. ACM (2009)
Marcenaro, L., Vernazza, G., Regazzoni, C.S.: Image stabilization algorithms for video-surveillance applications. In: Proceedings of 2001 International Conference on Image Processing, vol. 1, pp. 349–352. IEEE (2001)
Niskanen, M., Silvén, O., Tico, M.: Video stabilization performance assessment. In: 2006 IEEE International Conference on Multimedia and Expo, pp. 405–408. IEEE (2006)
Liu, S., Tan, P., Yuan, L., Sun, J., Zeng, B.: Meshflow: minimum latency online video stabilization. In: European Conference on Computer Vision, pp. 800–815. Springer (2016)
Zhang, L., Chen, X.Q., Kong, X.Y., Huang, H.: Geodesic video stabilization in transformation space. IEEE Trans. Image Process. 26(5), 2219–2229 (2017)
Liu, F., Gleicher, M., Wang, J., Jin, H., Agarwala, A.: Subspace video stabilization. ACM Trans. Graph. (TOG) 30(1), 4 (2011)
Matsushita, Y., Ofek, E., Ge, W., Tang, X., Shum, H.Y.: Full-frame video stabilization with motion inpainting. IEEE Trans. Pattern Anal. Mach. Intell. 28(7), 1150–1163 (2006)
Safdarnejad, S.M., Atoum, Y., Liu, X.: Temporally robust global motion compensation by keypoint-based congealing. In: European Conference on Computer Vision, pp. 101–119. Springer (2016)
Grundmann, M., Kwatra, V., Castro, D., Essa, I.: Calibration-free rolling shutter removal. In: 2012 IEEE International Conference on Computational Photography (ICCP), pp. 1–8. IEEE (2012)
Forssén, P.E., Ringaby, E.: Rectifying rolling shutter video from hand-held devices. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 507–514. IEEE (2010)
Karpenko, A., Jacobs, D., Baek, J., Levoy, M.: Digital video stabilization and rolling shutter correction using gyroscopes. CSTR 1, 2 (2011)
Morimoto, C., Chellappa, R.: Evaluation of image stabilization algorithms. In: Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 5, pp. 2789–2792. IEEE (1998)
St-Charles, P.L., Bilodeau, G.A., Bergevin, R.: Subsense: a universal change detection method with local adaptive sensitivity. IEEE Trans. Image Process. 24(1), 359–373 (2015)
Farnebäck, G.: Two-frame motion estimation based on polynomial expansion. In: Scandinavian Conference on Image Analysis, pp. 363–370. Springer (2003)
Opencv: Optical flow. https://docs.opencv.org/3.3.1/d7/d8b/tutorial_py_lucas_kanade.html. Accessed 03 Aug 2018
changedetection.net. http://www.changedetection.net/. Accessed 08 Aug 2018
Video database. http://liushuaicheng.org/SIGGRAPH2013/database.html. Accessed 21 Feb 2018
Tanakian, M., Rezaei, M., Mohanna, F.: Camera motion modeling for video stabilization performance assessment. In: 2011 7th Iranian Machine Vision and Image Processing (MVIP), pp. 1–4. IEEE (2011)
Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–612 (2004)
Qu, H., Song, L., Xue, G.: Shaking video synthesis for video stabilization performance assessment. In: Visual Communications and Image Processing (VCIP), pp. 1–6. IEEE (2013)
Zhai, B., Zheng, J., Wang, Y., Zhang, C.: A multi-scale evaluation method for motion filtering in digital image stabilization. In: 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI), pp. 682–688. IEEE (2015)
Acknowledgments
This work was supported by Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea government (MSIT) (Tech Commercialization Supporting Business based on Research Institute-Academic Cooperation system).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Hossain, M.A., Huh, EN. (2019). A Novel Performance Metric for the Video Stabilization Method. In: Lee, S., Ismail, R., Choo, H. (eds) Proceedings of the 13th International Conference on Ubiquitous Information Management and Communication (IMCOM) 2019. IMCOM 2019. Advances in Intelligent Systems and Computing, vol 935. Springer, Cham. https://doi.org/10.1007/978-3-030-19063-7_38
Download citation
DOI: https://doi.org/10.1007/978-3-030-19063-7_38
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-19062-0
Online ISBN: 978-3-030-19063-7
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)