Results 211 to 220 of about 111,250 (255)

Cost-sensitive background subtraction

2013 IEEE International Conference on Image Processing, 2013
Foreground and background are treated without distinction at classification stage in most background subtraction algorithms. However, correct classification of foreground is the primary requirement, and thus misclassification costs of the two classes should be different.
Xiang Zhang 0006, Jian Cheng 0001, Zhi Liu 0003, Jie Yang 0002   +3 more
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Robust Estimation for Background Subtraction

First International Conference on Innovative Computing, Information and Control - Volume I (ICICIC'06), 2006
Background subtraction is a method typically used to segment moving regions in image sequences taken from a static camera by comparing each new frame to a model of the scene background. We present a novel robust estimators model and a background subtraction approach.
Hongxun Zhang, De Xu
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Evaluation of Background Subtraction Methods

2008 Digital Image Computing: Techniques and Applications, 2008
In this paper we evaluate and compare six well-known foreground from background subtraction methods against a standard database. To be able to compare these algorithms objectively, we have chosen three challengeable scenarios from this database. The algorithms were applied to image sequences of length 100 to 800 frames.
Sorayya Panahi, Samira Sheikhi, Shahrzad Hadadan, Niloofar Gheissari   +3 more
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Background Subtraction With Video Coding

IEEE Signal Processing Letters, 2013
The classic Gaussian mixture model is based on the statistical information of every pixel; it is not robust to light changes. Before analysing every pixel in videos, it must be decoded to raw videos. In this letter, the method combining video coding and the Gaussian mixture model together is proposed.
Zhenkun Huang, Ruimin Hu, Zhongyuan Wang 0001   +2 more
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Spatiotemporal Algorithm for Background Subtraction

2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07, 2007
Background modeling and subtraction is a fundamental task in many computer vision and video processing applications. We present a novel probabilistic background modeling and subtraction method that exploits spatial and temporal dependencies between pixels.
S. Derin Babacan, Thrasyvoulos N. Pappas
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Perception-Inspired Background Subtraction

IEEE Transactions on Circuits and Systems for Video Technology, 2013
Developing universal and context-invariant methods is one of the hardest challenges in computer vision. Background subtraction (BS), an essential precursor in most machine vision applications used for foreground detection, is no exception. Due to overreliance on statistical observations, most BS techniques show unpredictable behavior in dynamic ...
Mahfuzul Haque, M. Manzur Murshed
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Foreground-Adaptive Background Subtraction

IEEE Signal Processing Letters, 2009
Background subtraction is a powerful mechanism for detecting change in a sequence of images that finds many applications. The most successful background subtraction methods apply probabilistic models to background intensities evolving in time; nonparametric and mixture-of-Gaussians models are but two examples.
J. Mike McHugh, Janusz Konrad, Venkatesh Saligrama, Pierre-Marc Jodoin   +3 more
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Background Subtraction by Difference Clustering

2020
Previous approaches to background subtraction typically considered the problem as a classification of pixels over time. We frame the problem as clustering the difference vectors between pixels in the current frame and in the background image set, and present a novel background subtraction method called Difference Clustering.
Xuanyi Wu, Xin Gao, Chenqiu Zhao, Jiangzheng Wu, Anup Basu   +4 more
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A hybrid codebook background model for background subtraction

2011 IEEE Workshop on Signal Processing Systems (SiPS), 2011
Real-time segmentation of scene into foreground and background is an important issue for many applications. Different from previous codebook (CB) methods, this paper introduces a hybrid CB model by combining the mixture of Gaussian (MOG) method and the CB method.
I-Ting Sun, Shih-Chung Hsu, Chung-Lin Huang   +2 more
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Background subtraction using dual-class backgrounds

2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV), 2016
This paper presents a novel approach to background subtraction which aims to extract moving objects in video stream. To this end, a novel background model is proposed by using both working backgrounds and candidate backgrounds, which can be transferred to each other according to an adaptive mechanism.
Bingshu Wang, Wenqian Zhu, Song Tang, Yong Zhao 0010, Wenbin Zou   +4 more
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