Recognize multi-touch gestures by graph modeling and matching

Abstract : Extract the features for a multi-touch gesture is difficult due to the complex temporal and motion relations between multiple trajectories. In this paper we present a new generic graph model to quantify the shape, temporal and motion information from multi-touch gesture. To make a comparison between graph, we also propose a specific graph matching method based on graph edit distance. Results prove that our graph model can be fruitfully used for multi-touch gesture pattern recognition purpose with the classifier of graph embedding and SVM.
Keywords : multi-touch SVM
Type de document :
Communication dans un congrès
Céline Rémi; Lionel Prévost; Eric Anquetil. 17th Biennial Conference of the International Graphonomics Society, Jun 2015, Pointe-à-Pitre, Guadeloupe. 2015, Drawing, Handwriting Processing Analysis: New Advances and Challenges
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Dernière modification le : vendredi 16 novembre 2018 - 01:29:41
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  • HAL Id : hal-01165768, version 1

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Zhaoxin Chen, Eric Anquetil, Harold Mouchère, Christian Viard-Gaudin. Recognize multi-touch gestures by graph modeling and matching. Céline Rémi; Lionel Prévost; Eric Anquetil. 17th Biennial Conference of the International Graphonomics Society, Jun 2015, Pointe-à-Pitre, Guadeloupe. 2015, Drawing, Handwriting Processing Analysis: New Advances and Challenges. 〈hal-01165768〉

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