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- W2078077488 abstract "Meaningful Non-Verbal Communication (NVC) signals can be recognised by facial deformations based on video tracking. However, the geometric features previously used contain a significant amount of redundant or irrelevant information. A feature selection method is described for selecting a subset of features that improves performance and allows for the identification and visualisation of facial areas involved in NVC. The feature selection is based on a sequential backward elimination of features to find a effective subset of components. This results in a significant improvement in recognition performance, as well as providing evidence that brow lowering is involved in questioning sentences. The improvement in performance is a step towards a more practical automatic system and the facial areas identified provide some insight into human behaviour." @default.
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- W2078077488 date "2013-04-01" @default.
- W2078077488 modified "2023-09-23" @default.
- W2078077488 title "Improving recognition and identification of facial areas involved in Non-Verbal Communication by feature selection" @default.
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- W2078077488 doi "https://doi.org/10.1109/fg.2013.6553764" @default.
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