• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
    https://jics.or.kr/
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Feature point extraction using scale-space filtering and Tracking algorithm based on comparing texturedness similarity


Yong-Hee Park, Oh-Seok Kwon, Journal of Internet Computing and Services, Vol. 6, No. 5, pp. 85-96, Oct. 2005
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Keywords: Scale-Space Filtering, Feature Point Extraction, Corner Detection, Feature Tracking, Motion Analysis

Abstract

This study proposes a method of feature point extraction using scale-space filtering and a feature point tracking algorithm based on a texturedness similarity comparison, With well-defined operators one can select a scale parameter for feature point extraction; this affects the selection and localization of the feature points and also the performance of the tracking algorithm. This study suggests a feature extraction method using scale-space filtering, With a change in the camera's point of view or movement of an object in sequential images, the window of a feature point will have an affine transform. Traditionally, it is difficult to measure the similarity between correspondence points, and tracking errors often occur. This study also suggests a tracking algorithm that expands Shi-Tomasi-Kanade's tracking algorithm with texturedness similarity.


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Cite this article
[APA Style]
Park, Y. & Kwon, O. (2005). Feature point extraction using scale-space filtering and Tracking algorithm based on comparing texturedness similarity. Journal of Internet Computing and Services, 6(5), 85-96.

[IEEE Style]
Y. Park and O. Kwon, "Feature point extraction using scale-space filtering and Tracking algorithm based on comparing texturedness similarity," Journal of Internet Computing and Services, vol. 6, no. 5, pp. 85-96, 2005.

[ACM Style]
Yong-Hee Park and Oh-Seok Kwon. 2005. Feature point extraction using scale-space filtering and Tracking algorithm based on comparing texturedness similarity. Journal of Internet Computing and Services, 6, 5, (2005), 85-96.