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» Robust Computer Vision through Kernel Density Estimation
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ICPR
2008
IEEE
14 years 6 months ago
Kernel bandwidth estimation in methods based on probability density function modelling
In kernel density estimation methods, an approximation of the data probability density function is achieved by locating a kernel function at each data location. The smoothness of ...
Adrian G. Bors, Nikolaos Nasios
ECCV
2004
Springer
14 years 7 months ago
A Robust Probabilistic Estimation Framework for Parametric Image Models
Models of spatial variation in images are central to a large number of low-level computer vision problems including segmentation, registration, and 3D structure detection. Often, i...
Maneesh Kumar Singh, Himanshu Arora, Narendra Ahuj...
BCS
2008
13 years 6 months ago
Fast Estimation of Nonparametric Kernel Density Through PDDP, and its Application in Texture Synthesis
In this work, a new algorithm is proposed for fast estimation of nonparametric multivariate kernel density, based on principal direction divisive partitioning (PDDP) of the data s...
Arnab Sinha, Sumana Gupta
ECCV
2010
Springer
13 years 10 months ago
Single Image Deblurring Using Motion Density Functions
Abstract. We present a novel single image deblurring method to estimate spatially non-uniform blur that results from camera shake. We use existing spatially invariant deconvolution...
CVPR
2004
IEEE
14 years 7 months ago
Motion-Based Background Subtraction Using Adaptive Kernel Density Estimation
Background modeling is an important component of many vision systems. Existing work in the area has mostly addressed scenes that consist of static or quasi-static structures. When...
Anurag Mittal, Nikos Paragios