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ACCV
2006
Springer
15 years 4 months ago
A Multiscale Co-linearity Statistic Based Approach to Robust Background Modeling
Background subtraction is an essential task in several static camera based computer vision systems. Background modeling is often challenged by spatio-temporal changes occurring due...
Prithwijit Guha, Dibyendu Palai, K. S. Venkatesh, ...
82
Voted
DPHOTO
2009
189views Hardware» more  DPHOTO 2009»
14 years 8 months ago
Automatic background generation from a sequence of images based on robust mode estimation
In this paper, we present a novel method for generating a background model from a sequence of images with moving objects. Our approach is based on non-parametric statistics and ro...
Desire Sidibé, Olivier Strauss, William Pue...
CVPR
2003
IEEE
16 years 7 days ago
Man-Made Structure Detection in Natural Images using a Causal Multiscale Random Field
This paper presents a generative model based approach to man-made structure detection in 2D natural images. The proposed approach uses a causal multiscale random field suggested i...
Sanjiv Kumar, Martial Hebert
94
Voted
DICTA
2003
14 years 11 months ago
Background Modeling and Subtraction Using a Local-linear-dependence-based Cauchy Statistical Model
:Many motion object detection algorithms rely on the process of background subtraction, an important technique which is used for detecting changes from a model of the background ...
Ying Ming, Jingjue Jiang, Jun Ming
BMCBI
2007
115views more  BMCBI 2007»
14 years 10 months ago
How accurate and statistically robust are catalytic site predictions based on closeness centrality?
Background: We examine the accuracy of enzyme catalytic residue predictions from a network representation of protein structure. In this model, amino acid α-carbons specify vertic...
Eric Chea, Dennis R. Livesay