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BMVC
2010

Label propagation in complex video sequences using semi-supervised learning

11 years 7 months ago
Label propagation in complex video sequences using semi-supervised learning
We propose a novel directed graphical model for label propagation in lengthy and complex video sequences. Given hand-labelled start and end frames of a video sequence, a variational EM based inference strategy propagates either one of several class labels or assigns an unknown class (void) label to each pixel in the video. These labels are used to train a multi-class classifier. The pixel labels estimated by this classifier are injected back into the Bayesian network for another iteration of label inference. The novel aspect of this iterative scheme, as compared to a recent approach [1], is its ability to handle occlusions. This is attributed to a hybrid of generative propagation and discriminative classification in a pseudo time-symmetric video model. The end result is a conservative labelling of the video; large parts of the static scene are labelled into known classes, and a void label is assigned to moving objects and remaining parts of the static scene. These labels can be used a...
Ignas Budvytis, Vijay Badrinarayanan, Roberto Cipo
Added 10 Feb 2011
Updated 10 Feb 2011
Type Journal
Year 2010
Where BMVC
Authors Ignas Budvytis, Vijay Badrinarayanan, Roberto Cipolla
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