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» On-Line Adaptive Background Modelling for Audio Surveillance
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ICMCS
2005
IEEE
105views Multimedia» more  ICMCS 2005»
13 years 11 months ago
Persistent audio modelling for background determination
This paper is concerned with modelling background audio online to detect foreground sounds in complex audio environments for surveillance and smart home applications. We examine a...
Simon Moncrieff, Svetha Venkatesh, Geoff A. W. Wes...
ICIP
2004
IEEE
14 years 7 months ago
Simultaneous background and foreground modeling for tracking in surveillance video
We present a stochastic tracking algorithm for surveillance video where targets are dim and at low resolution. The algorithm builds motion models for both background and foregroun...
Jie Shao, Shaohua Kevin Zhou, Rama Chellappa
ICASSP
2009
IEEE
14 years 2 days ago
A semi-supervised learning approach to online audio background detection
We present a framework for audio background modeling of complex and unstructured audio environments. The determination of background audio is important for understanding and predi...
Selina Chu, Shrikanth S. Narayanan, C.-C. Jay Kuo
ICMCS
2006
IEEE
215views Multimedia» more  ICMCS 2006»
13 years 11 months ago
Experiential Sampling based Foreground/Background Segmentation for Video Surveillance
Segmentation of foreground and background has been an important research problem arising out of many applications including video surveillance. A method commonly used for segmenta...
Pradeep K. Atrey, Vinay Kumar, Anurag Kumar, Mohan...
CAIP
2003
Springer
176views Image Analysis» more  CAIP 2003»
13 years 10 months ago
Evaluation of an Adaptive Composite Gaussian Model in Video Surveillance
Video surveillance systems seek to automatically identify events of interest in a variety of situations. Extracting a moving object from background is the most important step of t...
Qi Zang, Reinhard Klette