MULTI DIMENSIONAL DYNAMIC SCENE ANALYSIS. MULTIDIMENSIONAL IMAGE OBJECT SEGMENTATION AND TARGET TRACKING

Authors

  • Panayot Iliev
  • Plamen Tzvetkov
  • George Petrov

DOI:

https://doi.org/10.47839/ijc.6.3.448

Keywords:

Object tracking, video compression

Abstract

This paper presents an unconventional approach for object racking using image statistical criteria and 3D image entropy sequence analysis. The experimental results prove that the relationship between statistical characteristics of the 3D image entropy sequences and process of motion estimation is a guarantee for creating reliable and high precision target detection and tracking system. Using 2D and 3D multistage entropy functions analysis provide us a better way to reduce sequence channels for tracking moving and non moving objects. Vector based approach is used for object searching and detection inside image sequences. This way we provide necessary information for object based image sequences compression format that is much more efficient than standard MGEG video stream. Object based compression format is much more acceptable for high demanding security and military systems.

References

T. Huang, Image Sequence Analysis, Springer, Berlin, 1981.

T. Huang, Sequence Processing and Dynamic Scene Analysis, NATO ASI Series, Springer, Berlin, 1983.

P. Iliev and L. Tsekov, “Motion Detection Using Image Histogram Sequence Analysis, Signal Processing, vol. 30, Elsevier Science Publisher B. V., 1993, pp 373-384.

P. Iliev, Tzvetkov P., Petrov G., Proceedings of the Third IEEE Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS’2005, Sofia, Bulgaria, September 5-7, 2005, pp.596-601.

Alexander Strehl, J.K. Aggarwal, “Motion-based object detection and pose estimation method for airborne FLIR sequences”, 2000.

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Published

2014-08-01

How to Cite

Iliev, P., Tzvetkov, P., & Petrov, G. (2014). MULTI DIMENSIONAL DYNAMIC SCENE ANALYSIS. MULTIDIMENSIONAL IMAGE OBJECT SEGMENTATION AND TARGET TRACKING. International Journal of Computing, 6(3), 30-37. https://doi.org/10.47839/ijc.6.3.448

Issue

2007, Volume 6, Issue 3

Section

Articles

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