Paper Info
Title
Robust visual voice activity detection using local variance histogram in vehicular environments
Abstract
In this paper, a Vision based Voice Activity Detection (VVAD) algorithm is proposed using Local Variance Histogram (LVH). In conventional VVAD algorithm, the motion measure such as optical flow and intensity histogram are widely used. However, this approach is unstable under varying illumination and global motion changes which frequently occur in moving vehicular environment. To mitigate this problem, an appropriate framework based on LVH feature is developed. Comparison with two other conventional visual voice activity detectors shows the proposed method to be consistently more accurate and yields a substantial improvement in terms of detection probability and false alarm rate.
Year
DOI
Venue
2015
10.1109/ICCE.2015.7066482
ICCE
Keywords
Field
DocType
image motion analysis,speech processing,video signal processing,lvh feature,vvad algorithm,detection probability,false alarm rate,local variance histogram,motion measure,vehicular environment,visual voice activity detection,speech,histograms,robustness,hidden markov models,visualization
Histogram,Computer vision,Pattern recognition,Computer science,Visualization,Voice activity detection,Histogram matching,Robustness (computer science),Artificial intelligence,Constant false alarm rate,Hidden Markov model,Optical flow
Conference
ISSN
Citations 
PageRank 
2158-3994
0
0.34
References 
Authors
5
5
Name
Order
Citations
PageRank
kyungsun lee110.70
Taeyup Song2213.73
Sungsoo Kim311524.95
David K. Han421627.96
Hanseok Ko542180.24