Abstract
In this paper, a novel compressed domain method for classifying zooming motion is presented. Camera zoom motion classification is an important problem in video analysis wherein the task is to recognize and separate zooming-in camera from zooming-out camera. In our study, we address this problem utilizing local tetra patterns which has earlier found applications in image texture analysis and content-based image retrieval. Towards this goal we model the motion vector orientation and magnitude using local tetra patterns followed by histogram formation. Since the feature dimension is large, uniform pattern-based feature reduction is applied on the histograms to form the feature vector which is fed to the C-SVM classifier for training/testing purposes. Experimental testing utilizing standard video sequences with block motion vectors coming from exhaustive search motion estimation algorithm as well as H.264 obtained block motion vectors along with comparative analysis carried out with existing techniques shows superior performance for the proposed method.
Similar content being viewed by others
References
Chang, C.-C., Lin, C.-J.: LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. 2, 27:1–27:27 (2011)
Chen, Y.M., Bajic, I.V.: Motion vector outlier rejection cascade for global motion estimation. IEEE Signal Process. Lett. 17(2), 197–200 (2010)
Deng, Y., Manjunath, B.S.: Content-based search of video using color, texture, and motion. In: Proceedings of International Conference on Image Processing, vol. 2, pp. 534–537 (1997)
Duan, L.-Y., Jin, J.S., Tian, Q., Xu, C.-S.: Nonparametric motion characterization for robust classification of camera motion patterns. IEEE Trans. Multimed. 8(2), 323–340 (2006)
Hasan, M.A., Xu, M., He, X., Xu, C.: CAMHID: camera motion histogram descriptor and its application to cinematographic shot classification. IEEE Trans. Circuits Syst. Video Technol. 24(10), 1682–1695 (2014)
Huang, A.M., Nguyen, T.Q.: A multistage motion vector processing method for motion-compensated frame interpolation. IEEE Trans. Image Process. 17(5), 694–708 (2008)
Jin, R., Qi, Y., Hauptmann, A.: A probabilistic model for camera zoom detection. In: 16th IEEE International Conference on Pattern Recognition, vol. 3, pp. 859–862 (2002)
Kilicarslan, M., Zheng, J.Y.: Predict vehicle collision by TTC from motion using a single video camera. IEEE Tran. Intell. Transp. Syst. (2018). https://doi.org/10.1109/TITS.2018.2819827
Kim, H.-S., Lee, J.-H., Kim, C.-K., Kim, B.-G.: Zoom motion estimation using block-based fast local area scaling. IEEE Trans. Circuits Syst. Video Technol. 22(9), 1280–1291 (2012)
Lee, S., Hayes, M.H.: Real-time camera motion classification for content-based indexing and retrieval using templates. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. IV–3664–IV–3667 (2002)
Liao, S., Law, M.W.K., Chung, A.C.S.: Dominant local binary patterns for texture classification. IEEE Trans. Image Process. 18(5), 1107–1118 (2009)
Lin, C.C., Pankanti, S., Ashour, G., Porat, D., Smith, J.R.: Moving camera analytics: emerging scenarios, challenges, and applications. IBM J. Res. Dev. 59(2/3), 5:1–5:10 (2015)
Luo, J., Papin, C., Costello, K.: Towards extracting semantically meaningful key frames from personal video clips: from humans to computers. IEEE Trans. Circuits Syst. Video Technol. 19(2), 289–301 (2009)
Murala, S., Maheshwari, R.P., Balasubramanian, R.: Local tetra patterns: a new feature descriptor for content-based image retrieval. IEEE Trans. Image Process. 21(5), 2874–2886 (2012)
Okade, M., Patel, G., Biswas, P.K.: Robust learning-based camera motion characterization scheme with applications to video stabilization. IEEE Trans. Circuits Syst. Video Technol. 26(3), 453–466 (2016)
Po, L.-M., Wong, K.-M., Cheung, K.-W., Ng, K.-H.: Subsampled block-matching for zoom motion compensated prediction. IEEE Trans. Circuits Syst. Video Technol. 20(11), 1625–1637 (2010)
The H.264/AVC JM Reference Software
Wiegand, T., Sullivan, G.J., Bjontegaard, G., Luthra, A.: Overview of the H.264/AVC video coding standard. IEEE Trans. Circuits Syst. Video Technol. 13(7), 560–576 (2003)
Yuan, H., Chang, Y., Lu, Z., Ma, Y.: Model based motion vector predictor for zoom motion. IEEE Signal Process. Lett. 17(9), 787–790 (2010)
Acknowledgements
This work is supported by SERB, Government of India, under Grant Number: ECR/2016/000112. The authors would like to thank the anonymous reviewers for their valuable feedback which helped us to improve the paper.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Kesana, V., Okade, M. Compressed domain zoom motion classification using local tetra patterns. SIViP 13, 879–885 (2019). https://doi.org/10.1007/s11760-019-01424-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11760-019-01424-5