کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
526088 869061 2011 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Stochastic approximation for background modelling
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Stochastic approximation for background modelling
چکیده انگلیسی

Many background modelling approaches are based on mixtures of multivariate Gaussians with diagonal covariance matrices. This often yields good results, but complex backgrounds are not adequately captured, and post-processing techniques are needed. Here we propose the use of mixtures of uniform distributions and multivariate Gaussians with full covariance matrices. These mixtures are able to cope with both dynamic backgrounds and complex patterns of foreground objects. A learning algorithm is derived from the stochastic approximation framework, which has a very reduced computational complexity. Hence, it is suited for real time applications. Experimental results show that our approach outperforms the classic procedure in several benchmark videos.

Research highlights
► Mixtures of uniform distributions and multivariate Gaussians with full covariance matrices are proposed for background modelling.
► A learning algorithm is derived from the stochastic approximation framework, which has a reduced computational complexity.
► Real time requirements are fulfilled by this background detection approach.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Vision and Image Understanding - Volume 115, Issue 6, June 2011, Pages 735–749
نویسندگان
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