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Nesne takibi için histogram ilintisi temelli sınıflandırıcı birleşimi (Histogram correlation based classifier fusion for object tracking)

Topkaya, İbrahim Saygın and Erdoğan, Hakan (2011) Nesne takibi için histogram ilintisi temelli sınıflandırıcı birleşimi (Histogram correlation based classifier fusion for object tracking). In: IEEE 19th Conference on Signal Processing and Communications Applications (SIU 2011), Kemer, Antalya

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Official URL: http://dx.doi.org/10.1109/SIU.2011.5929672

Abstract

Mean shift is a popular method used in object tracking. The method, which relies on shifting the search area to the weight center of a generated “weight image” to track objects between consecutive frames, acquired a classifier based framework by using classifiers to generate the weight image. In this work, using multiple classifiers to generate the weight image and calculating contributions of the independent classifiers dynamically by using correlations between histograms of their weight images and histogram of a defined ideal weight image are presented.

Item Type:Papers in Conference Proceedings
Uncontrolled Keywords:consecutive frames , histogram correlation , image classification , image fusion , mean shift method , object tracking , weight image generation
Subjects:UNSPECIFIED
ID Code:18538
Deposited By:Hakan Erdoğan
Deposited On:24 Dec 2011 21:20
Last Modified:24 Dec 2011 21:20

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