Memory conscious sketched symbol recognition

Tırkaz, Çağlar and Yanıkoğlu, Berrin and Sezgin, T. Metin (2012) Memory conscious sketched symbol recognition. In: 21st International Conference on Pattern Recognition (ICPR 2012), Tsukuba City, Japan

Full text not available from this repository. (Request a copy)


Automatic sketch recognition is used to enhance human-computer interaction by allowing a natural/free form of interaction. It is a challenging problem due to the variability in hand drawings, the variation in the order of strokes, and the similarity of symbol classes. Since sketch recognition requires real time processing, the speed of the classifier is important. Another important issue is how to deal with very large data sets and/or large number of classes, as these also effect training and testing speed, making certain approaches infeasible. In order to deal with these issues, we present a memory conscious sketch recognition system that processes the data to retain only a few templates per class as prototypes; and furthermore, the query and prototypes are subsampled without loosing important information. The system also uses a cascaded combination of classifiers, to improve speed, as well as increase recognition accuracy. Results obtained using the public COAD and NicIcon databases are comparable to previous results obtained for these databases.
Item Type: Papers in Conference Proceedings
Uncontrolled Keywords: Handwriting Recognition, Human Computer Interaction, Machine Learning and Data Mining
Subjects: Q Science > QA Mathematics > QA075 Electronic computers. Computer science
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Computer Science & Eng.
Faculty of Engineering and Natural Sciences
Depositing User: Berrin Yanıkoğlu
Date Deposited: 06 Dec 2012 16:22
Last Modified: 26 Apr 2022 09:08

Actions (login required)

View Item
View Item