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The Fusion of Deep Learning Architectures and Particle Filtering Applied to Lip Tracking

10 years 1 months ago
The Fusion of Deep Learning Architectures and Particle Filtering Applied to Lip Tracking
This work introduces a new pattern recognition model for segmenting and tracking lip contours in video sequences. We formulate the problem as a general nonrigid object tracking method, where the computation of the expected segmentation is based on a filtering distribution. This is a difficult task because one has to compute the expected value using the whole parameter space of segmentation. As a result, we compute the expected segmentation using sequential Monte Carlo sampling methods, where the filtering distribution is approximated with a proposal distribution to be used for sampling. The key contribution of this paper is the formulation of this proposal distribution using a new observation model based on deep belief networks and a new transition model. The efficacy of the model is demonstrated in publicly available databases of video sequences of people talking and singing. Our method produces results comparable to state-of-the-art models, but showing potential to be more robust to...
Gustavo Carneiro, Jacinto Nascimento
Added 02 Sep 2010
Updated 02 Sep 2010
Type Conference
Year 2010
Where ICPR
Authors Gustavo Carneiro, Jacinto Nascimento
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