Human Detection Using Surf and Sift Feature Extraction Methods in Different Color Spaces


Authors

Osameh Biglari - Taali university, Qom, Iran. Reza Ahsan - Islamic Azad University, Qom branch, Iran. Majid Rahi - Pardisan University, Mazandaran, Feridonkenar, Iran.


Abstract

Local feature matching has become a commonly used method to compare images. For tracking and human detection, a reliable method for comparing images can constitute a key component for localization and loop closing tasks. two different types of image feature algorithms, Scale - Invariant Feature Transform (SIFT) and the more recent Speeded Up Robust Features (SURF), have been used to compare the images. In this paper, we propose the use of a rich set of feature descriptors based on SIFT and SURF in the different color spaces.


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ISRP Style

Osameh Biglari, Reza Ahsan, Majid Rahi, Human Detection Using Surf and Sift Feature Extraction Methods in Different Color Spaces , Journal of Mathematics and Computer Science, 11 (2014), no. 2, 111 - 122

AMA Style

Biglari Osameh, Ahsan Reza, Rahi Majid, Human Detection Using Surf and Sift Feature Extraction Methods in Different Color Spaces . J Math Comput SCI-JM. (2014); 11(2):111 - 122

Chicago/Turabian Style

Biglari, Osameh, Ahsan, Reza, Rahi, Majid. "Human Detection Using Surf and Sift Feature Extraction Methods in Different Color Spaces ." Journal of Mathematics and Computer Science, 11, no. 2 (2014): 111 - 122


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