On-Line Sketch Recognition Using Direction Feature

Abstract : Sketch recognition is widely used in pen-based interaction, especially as the increasing popularity of devices with touch screens. It can enhance human-computer interaction by allowing a natural/free form of interaction. The main challenging problem is the variability in hand drawings. This paper presents an on-line sketch recognition method based on the direction feature. We also present two feature representations to train a classifier. We support our case by experimental results obtained from the NicIcon database. A recognition rate of 97.95% is achieved, and average runtime is 97.6ms using a Support Vector Machine classifier.
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Paula Kotzé; Gary Marsden; Gitte Lindgaard; Janet Wesson; Marco Winckler. 14th International Conference on Human-Computer Interaction (INTERACT), Sep 2013, Cape Town, South Africa. Springer, Lecture Notes in Computer Science, LNCS-8119 (Part III), pp.259-266, 2013, Human-Computer Interaction – INTERACT 2013. 〈10.1007/978-3-642-40477-1_16〉
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Wei Deng, Lingda Wu, Ronghuan Yu, Jiazhe Lai. On-Line Sketch Recognition Using Direction Feature. Paula Kotzé; Gary Marsden; Gitte Lindgaard; Janet Wesson; Marco Winckler. 14th International Conference on Human-Computer Interaction (INTERACT), Sep 2013, Cape Town, South Africa. Springer, Lecture Notes in Computer Science, LNCS-8119 (Part III), pp.259-266, 2013, Human-Computer Interaction – INTERACT 2013. 〈10.1007/978-3-642-40477-1_16〉. 〈hal-01504888〉

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