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» Novelty Detection in Image Sequences with Dynamic Background
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ICIP
2006
IEEE
14 years 9 months ago
Background Modeling from GMM Likelihood Combined with Spatial and Color Coherency
This paper proposes to combine spatial and color coherency with the pixel-wise GMM to determine the background model. We first represent each pixel with a hybrid feature vector, w...
Sheng-Yan Yang, Chiou-Ting Hsu
ICPR
2008
IEEE
14 years 2 months ago
Monocular video foreground segmentation system
This paper proposes an automatic foreground segmentation system based on Gaussian mixture models and dynamic graph cut algorithm. An adaptive perpixel background model is develope...
Xiaoyu Wu, Yangsheng Wang, Xiaolong Zheng
ACCV
2006
Springer
14 years 1 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, ...
ICPR
2010
IEEE
13 years 5 months ago
Robust Foreground Object Segmentation via Adaptive Region-Based Background Modelling
We propose a region-based foreground object segmentation method capable of dealing with image sequences containing noise, illumination variations and dynamic backgrounds (as often...
Vikas Reddy, Conrad Sanderson, Brian C. Lovell
DAGM
2009
Springer
14 years 2 months ago
Multi-view Object Detection Based on Spatial Consistency in a Low Dimensional Space
This paper describes a new approach for detecting objects based on measuring the spatial consistency between different parts of an object. These parts are pre-defined on a set of...
Gurman Gill, Martin Levine