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
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https://hal.univ-antilles.fr/hal-01165768
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Zhaoxin Chen, Eric Anquetil, Harold Mouchère, Christian Viard-Gaudin. Recognize multi-touch gestures by graph modeling and matching. 17th Biennial Conference of the International Graphonomics Society, International Graphonomics Society (IGS); Université des Antilles (UA), Jun 2015, Pointe-à-Pitre, Guadeloupe. ⟨hal-01165768⟩

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