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» Feature versus model based noise robustness
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ACCV
2006
Springer
13 years 10 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, ...
MM
1999
ACM
126views Multimedia» more  MM 1999»
13 years 9 months ago
Robust color indexing
In content based image retrieval, color indexing is one of the most prevalent retrieval methods. In literature, most of the attention has been focussed on the color model with lit...
Nicu Sebe, Michael S. Lew
ICMI
2004
Springer
281views Biometrics» more  ICMI 2004»
13 years 10 months ago
Articulatory features for robust visual speech recognition
Visual information has been shown to improve the performance of speech recognition systems in noisy acoustic environments. However, most audio-visual speech recognizers rely on a ...
Kate Saenko, Trevor Darrell, James R. Glass
ICASSP
2011
IEEE
12 years 8 months ago
Structured discriminative models for noise robust continuous speech recognition
Recently there has been interest in structured discriminative models for speech recognition. In these models sentence posteriors are directly modelled, given a set of features ext...
Anton Ragni, Mark John Francis Gales
ICPR
2010
IEEE
13 years 6 months ago
Noise-Robust Voice Activity Detector Based on Hidden Semi-Markov Models
This paper concentrates on speech duration distributions that are usually invariant to noises and proposes a noise-robust and real-time voice activity detector (VAD) using the hid...
Xianglong Liu, Yuan Liang, Yihua Lou, He Li, Baoso...