Abstract
This paper presents a fast algorithm for object tracking in an image sequence. It is a method that models the borders of the image as one-dimensional histograms which are then used instead of templates in the matching procedure. The algorithm models the item being tracked as well as the background in the vicinity so as to then suppress it. It uses cross correlation to find the best match and weighted average to renew the model.
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Curetti, M., Bravo, S.G., Arri, G.S., Mathé, L. (2012). Fast Tracking Algorithm with Borders 1-D Histogram Correlation. In: Alvarez, L., Mejail, M., Gomez, L., Jacobo, J. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2012. Lecture Notes in Computer Science, vol 7441. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33275-3_76
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DOI: https://doi.org/10.1007/978-3-642-33275-3_76
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