Sequential Monte Carlo video text segmentation

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Sequential Monte Carlo video text segmentation
This paper presents a probabilistic algorithm for segmenting and recognizing text embedded in video sequences. The algorithm approximates the posterior distribution of segmentation thresholds of video text by a set of weighted samples. After initialization the set of samples is recursively refined by random sampling under a temporal Bayesian framework. The proposed methodology allows us to estimate the optimal text segmentation parameters directly in function of the string recognition results instead of segmentation quality. Results on a database of 6944 images demonstrate the validity of the algorithm. 1
Datong Chen, Jean-Marc Odobez
Added 24 Oct 2009
Updated 27 Oct 2009
Type Conference
Year 2003
Where ICIP
Authors Datong Chen, Jean-Marc Odobez
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