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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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Submitted on : Saturday, June 20, 2015 - 12:58:24 AM
Last modification on : Wednesday, April 27, 2022 - 4:21:01 AM
Long-term archiving on: : Tuesday, September 15, 2015 - 7:46:28 PM


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  • HAL Id : hal-01165768, version 1


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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