Publication Type : Conference Proceedings
Publisher : Springer
Source : In Mathematical Modeling and Scientific Computation, Springer, p.413-420 (2012)
Url : https://link.springer.com/chapter/10.1007/978-3-642-28926-2_45
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Verified : Yes
Year : 2012
Abstract : This paper presents a modified Speeded Up Robust Features (SURF) with feature point detector based on scale space saddle points. Most of the feature detectors like Scale Invariant Feature Transform (SIFT), Principal Component Analysis (PCA)–SIFT and SURF are based on extrema points i.e. local maxima and minima. This work aims at utilizing the saddle points for panorama stitching which is a common and direct application for feature matching. Here Euclidean distance of descriptor is used to find the correct matches. Experiments to test the performance are done on Oxford affine covariant dataset and compared the performance with that of SURF.
Cite this Research Publication : and Dr. Shunmuga Velayutham C., “SaddleSURF: A saddle based interest point detector (2012)”, In Mathematical Modeling and Scientific Computation. Springer, pp. 413-420, 2012.