Visual Recognition of Sketched Symbols

Diagrams are an essential means of capturing and communicating information in many different domains. They are also a valuable part of the early design process, helping us explore ideas and solutions in an informal environment. This paper presents a new approach to sketched symbol recognition that preserves as much of the visual nature of the symbol as possible. Our method is robust to differences in drawing style, computationally efficient, and achieves excellent performance for several different domains. Author Keywords Sketch Recognition, symbol recognition, vision recognition algorithms

[1]  Randall Davis,et al.  Recognition of Hand Drawn Chemical Diagrams , 2007, AAAI.

[2]  Seiichi Uchida,et al.  Online character recognition using eigen-deformations , 2004, Ninth International Workshop on Frontiers in Handwriting Recognition.

[3]  L. Kara,et al.  Recognizing Multi-Stroke Symbols , 2002 .

[4]  James A. Landay,et al.  Visual similarity of pen gestures , 2000, CHI.

[5]  Anil K. Jain,et al.  A modified Hausdorff distance for object matching , 1994, Proceedings of 12th International Conference on Pattern Recognition.

[6]  Levent Burak Kara,et al.  An Image-Based Trainable Symbol Recognizer for Sketch-Based Interfaces , 2004, AAAI Technical Report.

[7]  Stuart Russell,et al.  Statistical Visual Language Models for Ink Parsing , 2002 .

[8]  Anil K. Jain,et al.  Template-based online character recognition , 2001, Pattern Recognit..

[9]  Uchida Seiichi,et al.  Online Character Recognition Using Eigen-Deformations , 2004 .

[10]  Hermann Ney,et al.  Local context in non-linear deformation models for handwritten character recognition , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[11]  Michael Oltmans Envisioning sketch recognition: a local feature based approach to recognizing informal sketches , 2007 .

[12]  Yann LeCun,et al.  The mnist database of handwritten digits , 2005 .

[13]  Yoshua Bengio,et al.  LeRec: A NN/HMM Hybrid for On-Line Handwriting Recognition , 1995, Neural Computation.

[14]  Ethem Alpaydin,et al.  Combining multiple representations and classifiers for pen-based handwritten digit recognition , 1997, Proceedings of the Fourth International Conference on Document Analysis and Recognition.

[15]  A. Newton,et al.  Sketched symbol recognition using Zernike moments , 2004, ICPR 2004.

[16]  Dean Rubine,et al.  Specifying gestures by example , 1991, SIGGRAPH.

[17]  Paul A. Viola,et al.  Recognition and grouping of handwritten text in diagrams and equations , 2004, Ninth International Workshop on Frontiers in Handwriting Recognition.

[18]  Yoshua Bengio,et al.  Gradient-based learning applied to document recognition , 1998, Proc. IEEE.

[19]  Claus Bahlmann,et al.  Online handwriting recognition with support vector machines - a kernel approach , 2002, Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition.

[20]  Claus Bahlmann,et al.  The writer independent online handwriting recognition system frog on hand and cluster generative statistical dynamic time warping , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[21]  Tracy Anne Hammond,et al.  LADDER: a language to describe drawing, display, and editing in sketch recognition , 2003, IJCAI.