IMAGE ANALYSIS

Video tracking using morphological pyramids

[+] Author Affiliations
C. Andrew Segall, Wei Chen, Scott T. Acton

School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, Oklahoma?74078

J. Electron. Imaging. 8(2), 176-184 (Apr 01, 1999). doi:10.1117/1.482689
History: Received Jan. 17, 1997; Revised Dec. 15, 1998; Accepted Dec. 30, 1998
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Abstract

In this paper, the utilization of morphological pyramids for object tracking is detailed. Image pyramids, constructed via morphological operations and subsampling, have been previously applied to the image compression and progressive transmission problems. We extend the application of the morphological pyramid to the video tracking problem—following the position of a previously identified moving object in a sequence of video frames. Morphological pyramids allow both a considerable tolerance of noise and a saving in computational time for video tracking. Experimental results from the application of the morphological pyramid to noisy IR image sequences are presented. Our results show that the computational efficiency of the morphological pyramid for tracking significantly improves upon the traditional fixed resolution approach by organizing a search from coarse to fine. Furthermore, the morphological pyramid significantly enhances performance over the comparable linear pyramid methods. © 1999 SPIE and IS&T.

© 1999 SPIE and IS&T

Topics

Video

Citation

C. Andrew Segall ; Wei Chen and Scott T. Acton
"Video tracking using morphological pyramids", J. Electron. Imaging. 8(2), 176-184 (Apr 01, 1999). ; http://dx.doi.org/10.1117/1.482689


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