Early Recognition of Handwritten Gestures based on Multi-classifier Reject Option - LS2N - équipe IPI ( Image Perception Interaction ) Accéder directement au contenu
Communication Dans Un Congrès Année : 2017

Early Recognition of Handwritten Gestures based on Multi-classifier Reject Option

Résumé

In this paper a multi-classifier method for early recognition of handwritten gesture is presented. Unlike the other works which study the early recognition problem related to the time, we propose to make the recognition according to the quantity of incremental drawing of handwritten gestures. We train a segment length based multi-classifier for the task of recognizing the handwritten touch gesture as early as possible. To deal with potential similar parts at the beginning of different gestures, we introduce a reject option to postpone the decision until ambiguity persists. We report results on two freely available datasets: MGSet and ILG. These results demonstrate the improvement we obtained by using the proposed reject option for the early recognition of handwritten gestures.
Fichier principal
Vignette du fichier
3586a212.pdf (1.28 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-01653154 , version 1 (05-12-2017)

Identifiants

Citer

Zhaoxin Chen, Harold Mouchère, Eric Anquetil, Christian Viard-Gaudin. Early Recognition of Handwritten Gestures based on Multi-classifier Reject Option. 14th IAPR International Conference on Document Analysis and Recognition (ICDAR2017), Nov 2017, Kyoto, Japan. ⟨10.1109/ICDAR.2017.43⟩. ⟨hal-01653154⟩
420 Consultations
144 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More