The variable bandwidth mean shift and data-driven scale selection
Top Cited Papers
- 13 November 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 1, 438-445 vol.1
- https://doi.org/10.1109/iccv.2001.937550
Abstract
We present two solutions for the scale selection problem in computer vision. The first one is completely nonparametric and is based on the the adaptive estimation of the normalized density gradient. Employing the sample point estimator, we define the Variable Bandwidth Mean Shift, prove its convergence, and show its superiority over the fixed bandwidth procedure. The second technique has a semiparametric nature and imposes a local structure on the data to extract reliable scale information. The local scale of the underlying density is taken as the bandwidth which maximizes the magnitude of the normalized mean shift vector. Both estimators provide practical tools for autonomous image and quasi real-time video analysis and several examples are shown to illustrate their effectiveness.Keywords
This publication has 19 references indexed in Scilit:
- Bilateral filtering for gray and color imagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Robust anisotropic diffusionIEEE Transactions on Image Processing, 1998
- Smoothing Methods in StatisticsPublished by Springer Nature ,1996
- Smoothing Bias in Density Derivative EstimationJournal of the American Statistical Association, 1993
- Multivariate Density EstimationPublished by Wiley ,1992
- Adaptive smoothing: a general tool for early visionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1991
- Scale-space and edge detection using anisotropic diffusionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1990
- Comparison of Data-Driven Bandwidth SelectorsJournal of the American Statistical Association, 1990
- Color information for region segmentationComputer Graphics and Image Processing, 1980
- Density Estimation for Statistics and Data AnalysisPublished by Springer Nature ,1400