Method of interest points characterization based C-HOG local descriptor

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Abstract

This article proposes an approach to detection and description of interest points based C-HOG. The study of two interest point local descriptor methods, the SIFT and the SURF, allows us to understand their construction and extracts the various advantages (invariances, speeds, repeatability). Our goal is to couple these advantages to create a new system (detector and descriptor). The latter must be as invariant as possible for the image transformation (rotations, scales, viewpoints). We will have to find a compromise between a good matching rate and the number of points matched. All the detector and descriptor parameters (orientations, thresholds, analysis pattern, parameters) will be also detailed in this article. © 2010 Springer-Verlag.

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Grand-Brochier, M., Tilmant, C., & Dhome, M. (2010). Method of interest points characterization based C-HOG local descriptor. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6455 LNCS, pp. 219–228). https://doi.org/10.1007/978-3-642-17277-9_23

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