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.
Type de document :
Communication dans un congrès
17th Biennial Conference of the International Graphonomics Society, Jun 2015, Pointe-à-Pitre, France
https://hal.archives-ouvertes.fr/hal-01243992
Contributeur : Zhaoxin Chen
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Soumis le : vendredi 18 décembre 2015 - 09:07:35
Dernière modification le : vendredi 16 novembre 2018 - 01:24:31
Document(s) archivé(s) le : samedi 19 mars 2016 - 10:31:43
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, Jun 2015, Pointe-à-Pitre, France. 〈hal-01243992〉
