DocumentCode :
153072
Title :
A probabilistic approach for fast covariance descriptor
Author :
Akbulut, O. ; Erturk, S.
Author_Institution :
Isaret ve Goruntu Isleme Laboratuvari (KULIS), Kocaeli Univ., Kocaeli, Turkey
fYear :
2014
fDate :
23-25 April 2014
Firstpage :
2166
Lastpage :
2169
Abstract :
In this paper, a low computational load based region covariance descriptor (RCD) approach has been proposed. The proposed method is based on using fewer feature vectors on construction of RCD. Number of feature vectors is reduced by utilizing the random pixel decimation pattern. By making use of the proposed method, fast covariance descriptor based object tracking has been carried out. As can be seen from the experimental results, the proposed method enables to perform fast RCD based object tracking without compromising relatively tracking quality.
Keywords :
covariance analysis; object tracking; probability; random processes; RCD approach; RCD based object tracking; computational load; feature vector; probabilistic approach; random pixel decimation pattern; region covariance descriptor approach; tracking quality; Computer vision; Conferences; Histograms; Object tracking; Pattern recognition; Signal processing; Vectors; Region covariance descriptor; object tracking; segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2014 22nd
Conference_Location :
Trabzon
Type :
conf
DOI :
10.1109/SIU.2014.6830692
Filename :
6830692
Link To Document :
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