A Hardware Architecture for Scale-space Extrema Detection

Vision based object recognition and localization have been studied widely in recent years. Often the initial step in such tasks is detection of interest points from a grey-level image. The current ...

[1]  Shintaro Izumi,et al.  A Low-Power Real-Time SIFT Descriptor Generation Engine for Full-HDTV Video Recognition , 2011, IEICE Trans. Electron..

[2]  J. Koenderink.  The structure of images , 2004, Biological Cybernetics.

[3]  Matthew A. Brown,et al.  Invariant Features from Interest Point Groups , 2002, BMVC.

[4]  Cordelia Schmid,et al.  Evaluation of Interest Point Detectors , 2000, International Journal of Computer Vision.

[5]  T. Lindeberg,et al.  Scale-Space Theory : A Basic Tool for Analysing Structures at Different Scales , 1994 .

[6]  Cordelia Schmid,et al.  A Performance Evaluation of Local Descriptors , 2005, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  José Hernández Palancar,et al.  A Hardware Architecture for SIFT Candidate Keypoints Detection , 2009, CIARP.

[8]  Yan Ke,et al.  PCA-SIFT: a more distinctive representation for local image descriptors , 2004, CVPR 2004.

[9]  Tony Lindeberg,et al.  Feature Detection with Automatic Scale Selection , 1998, International Journal of Computer Vision.

[10]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[11]  Matthijs C. Dorst.  Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[12]  George A. Constantinides,et al.  A Parallel Hardware Architecture for Scale and Rotation Invariant Feature Detection , 2008, IEEE Transactions on Circuits and Systems for Video Technology.

[13]  A. Vedaldi.  An implementation of SIFT detector and descriptor , 2008 .

[14]  Andrea Vedaldi,et al.  Vlfeat: an open and portable library of computer vision algorithms , 2010, ACM Multimedia.