Abstract
A technique of video sequence processing through the energy parameters analysis of video signal is discussed in this paper. The purpose of the analysis here is to determine the object movements in a real-life scene. The new technique is theoretically justified. It is based on the dependence of energy signal at the initial phase. The signal is represented as a spatial cosine segment. The differences of the energy characteristics are introduced to improve the efficiency of video sequences processing. An example of a video sequence processing of the real scene is considered. It is shown that if pixels orderly move inside the object, then the borders and the velocity of the moving object are well determined by using the characteristics difference. However, the pixels groups with the movement differ from the object movement can exist within the object boundaries. In this case, the pixels must be regularly zeroed out, starting from the vision area edges.
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References
Eckstein, M.P.: Visual search: a retrospective. J. Vis. 11(5), 1–36 (2011)
Bradley, C., Abrams, J., Geisler, W.S.: Retina-V1 model of delectability across the visual field. J. Vis. 14(22), 1–22 (2014)
Olmedo-Paya, A., Martinez-Alvarez, A., Cuenca-Asensi, S., Ferrandez-Visente, J.M., Fernandez, E.: Modeling the effect of fixational eye movements in natural scenes. In: Ferrandez Visente, J.M., Sánchez, J.R.A., de la Paz López, F., Moreo, F.J.T. (eds.) Natural and Artificial Models in Computation and Biology-1. LNCS, vol. 7930, pp. 332–341. Springer, Heidelberg (2013)
Jimenez, E.V.C., Navarro, D.Z.: Intelligent active vision systems for robots. Cuvillier, Göttingen (2007)
Cai, J., Pan, W.: On fast and accurate block-based motion estimation algorithms using particle swam optimization. Inf. Sci. 197, 53–64 (2012)
Ho, H., Klepko, R., Nam, N., Demin, W.: A high performance hardware architecture for multi-frame hierarchical motion estimation. IEEE Trans. Consum. Electron. 57(2), 794–801 (2011)
Srinivasarao, B.K.N., Chakrabarti, I.: A parallel architectural implementation of the fast three step search algorithm for block motion estimation. In: 5th International Multi-Conference on Systems, Signals and Devices, pp. 1–6. IEEE Press, Amman, USA (2008)
Lucas, B.D., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: 7th International Joint Conference on Artificial Intelligence, vol. 2, pp. 674–679. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA (1981)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60(2), 91–110 (2004)
Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-up robust features (SURF). Comput. Vis. Image Underst. 110(3), 346–359 (2008)
Reducindo, I., Arce-Santana, E., Campos-Delgado, D.U., Vigueras-Gomez, F.: Non-rigid multimodal image registration based on local variability measures and optical flow. In: Annual International Conference of the IEEE Engineering in Medicine and Biological Society, pp. 1133–1136. IEEE Press, San Diego, CA, USA. (2012)
Bogoslovsky, A.: Multidimensional signal processing. Radiotec, Moscow (in Russian) (2013)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Prentice Hall, Upper Saddle River (2002)
Jähne, B.: Digital Image Processing, 6th edn. Springer, Berlin (2005)
Bogoslovsky, A., Zhigulina, I.: A way of energy analysis for image and video sequence processing. In: Favorskaya, M.N., Jain, L.C. (eds.) Computer Vision in Control Systems-1. ISRL, vol. 73, pp. 183–210. Springer, Switzerland (2015)
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The work of the authors was supported by the Russian Fund of Basic Researches project No. 15-01-08043.
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Bogoslovsky, A., Zhigulina, I., Maslov, I., Mordovina, T. (2015). Frequency Characteristics for Video Sequences Processing. In: Damiani, E., Howlett, R., Jain, L., Gallo, L., De Pietro, G. (eds) Intelligent Interactive Multimedia Systems and Services. Smart Innovation, Systems and Technologies, vol 40. Springer, Cham. https://doi.org/10.1007/978-3-319-19830-9_14
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DOI: https://doi.org/10.1007/978-3-319-19830-9_14
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