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IEEE MultiMedia
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ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
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ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
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CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
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ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part I
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Pattern Recognition
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Proceedings of the 14th ACM international conference on Multimodal interaction
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There have been several studies that jointly use audio, lip intensity, and lip geometry information for speaker identification and speech-reading applications. This paper proposes using explicit lip motion information, instead of or in addition to lip intensity and/or geometry information, for speaker identification and speech-reading within a unified feature selection and discrimination analysis framework, and addresses two important issues: 1) Is using explicit lip motion information useful, and, 2) if so, what are the best lip motion features for these two applications? The best lip motion features for speaker identification are considered to be those that result in the highest discrimination of individual speakers in a population, whereas for speech-reading, the best features are those providing the highest phoneme/word/phrase recognition rate. Several lip motion feature candidates have been considered including dense motion features within a bounding box about the lip, lip contour motion features, and combination of these with lip shape features. Furthermore, a novel two-stage, spatial, and temporal discrimination analysis is introduced to select the best lip motion features for speaker identification and speech-reading applications. Experimental results using an hidden-Markov-model-based recognition system indicate that using explicit lip motion information provides additional performance gains in both applications, and lip motion features prove more valuable in the case of speech-reading application