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The role of grouping in sketched diagram recognition

Published:17 August 2018Publication History

ABSTRACT

An early step in bottom-up diagram recognition systems is grouping ink strokes into shapes. This paper gives an overview of the key literature on automatic grouping techniques in sketch recognition. In addition, we identify the major challenges in grouping ink into identifiable shapes, discuss the common solutions to these challenges based on current research, and highlight areas for future work.

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References

  1. Harold Mouchre Christian Viard-Gaudin Ahmad-Montaser Awal, Guihuan Feng. 2011. First experiments on a new online handwritten flowchart database. (2011).Google ScholarGoogle Scholar
  2. Christine Alvarado. 2007. Sketch recognition for digital circuit design in the classroom. In 2007 Invited Workshop on Pen-Centric Computing Research. Citeseer.Google ScholarGoogle Scholar
  3. Christine Alvarado and Randall Davis. 2004. SketchREAD: a multi-domain sketch recognition engine. In Proceedings of the 17th annual ACM symposium on User interface software and technology. ACM, 23--32. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Christine Alvarado and Randall Davis. 2006. Dynamically constructed bayes nets for multi-domain sketch understanding. In ACM SIGGRAPH 2006 Courses. ACM, 32. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Relja Arandjelović and Tevfik Metin Sezgin. 2011. Sketch recognition by fusion of temporal and image-based features. Pattern Recognition 44, 6 (2011), 1225--1234. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Martin Bresler. 2016. Online recognition of sketched arrow-connected diagrams. International Journal on Document Analysis and Recognition (IJDAR) 19, 3 (2016), 253fi?!267. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Martin Bresler, Daniel Prùša, and Václav Hlavác. 2013a. Modeling Flowchart Structure Recognition As a Max-Sum Problem. In Proceedings of the 2013 12th International Conference on Document Analysis and Recognition (ICDAR '13). IEEE Computer Society, Washington, DC, USA, 1215--1219. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Martin Bresler, Daniel Průša, and Václav Hlaváč. 2013b. Simultaneous Segmentation and Recognition of Graphical Symbols using a Composite Descriptor. In CVWW 2013: Proceedings of the 18th Computer Vision Winter Workshop, Walter G. Kropatsch, Geetha Ramachandran, and Fuensanta Torres (Eds.). Vienna University of Technology, Karlsplatz 13, Vienna, Austria, 16--23.Google ScholarGoogle Scholar
  9. Martin Bresler, Daniel Prusa, and Václav Hlavać. 2015a. Detection of arrows in on-line sketched diagrams using relative stroke positioning. In IEEE Winter Conference on Applications of Computer Vision. IEEE, 610--617. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Martin Bresler, Daniel Pruša, and Václav Hlavác. 2015b. Using agglomerative clustering of strokes to perform symbols over-segmentation within a diagram recognition system (CVWW). 67--74.Google ScholarGoogle Scholar
  11. Martin Bresler, Truyen Van Phan, Daniel Prusa, Masaki Nakagawa, and Vclav Hlavc. 2014. Recognition system for on-line sketched diagrams. In Frontiers in Handwriting Recognition (ICFHR), 2014 14th International Conference on. IEEE, 563--568.Google ScholarGoogle ScholarCross RefCross Ref
  12. Beibei Chao, Xiaoyan Zhao, Dapeng Shi, Guihuan Feng, and Bin Luo. 2017. Eyes Understand the Sketch!: Gaze-Aided Stroke Grouping of Hand-Drawn Flowcharts. In Proceedings of the 22Nd International Conference on Intelligent User Interfaces (IUI '17). ACM, New York, NY, USA, 79--83. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Gennaro Costagliola, Vincenzo Deufemia, and Michele Risi. 2005. Sketch grammars: A formalism for describing and recognizing diagrammatic sketch languages. In Eighth International Conference on Document Analysis and Recognition (ICDAR'05). IEEE, 1226--1230. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Gennaro Costagliola, Mattia De Rosa, and Vittorio Fuccella. 2014. Local context-based recognition of sketched diagrams. Journal of Visual Languages & Computing 25, 6 (2014), 955 -- 962. DOI:http://dx.doi.org/ Distributed Multimedia Systems DMS2014 Part I. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Gennaro Costagliola, Mattia De Rosa, and Vittorio Fuccella. 2015. Extending local context-based specifications of visual languages. Journal of Visual Languages & Computing 31 (2015), 184 -- 195. DOI:http://dx.doi.org/ Special Issue on DMS2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Adrien Delaye. 2014. Structured prediction models for online sketch recognition. Interpretation 1, 3 (2014), 4--16.Google ScholarGoogle Scholar
  17. Adrien Delaye and Kibok Lee. 2015. A flexible framework for online document segmentation by pairwise stroke distance learning. Pattern Recognition 48, 4 (2015), 1193--1206. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Vincenzo Deufemia, Michele Risi, and Genoveffa Tortora. 2014. Sketched Symbol Recognition Using Latent-Dynamic Conditional Random Fields and Distance-based Clustering. Pattern Recogn. 47, 3 (March 2014), 1159--1171. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Guihuan Feng, Christian Viard-Gaudin, and Zhengxing Sun. 2009. On-line Hand-drawn Electric Circuit Diagram Recognition Using 2D Dynamic Programming. Pattern Recogn. 42, 12 (Dec. 2009), 3215--3223. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Leslie Gennari, Levent Burak Kara, Thomas F Stahovich, and Kenji Shimada. 2005. Combining geometry and domain knowledge to interpret hand-drawn diagrams. Computers & Graphics 29, 4 (2005), 547--562. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Tracy Hammond and Brandon Paulson. 2011. Recognizing sketched multistroke primitives. ACM Transactions on Interactive Intelligent Systems (TiiS) 1, 1 (2011), 1--34. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Tracy A Hammond and Randall Davis. 2009. Recognizing interspersed sketches quickly. In Proceedings of Graphics Interface. Canadian Information Processing Society, 157--166. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. James Herold and Thomas F Stahovich. 2012. The 1 Recognizer: a fast, accurate, and easy-to-implement handwritten gesture recognition technique. In Proceedings - Sketch-Based Interfaces and Modeling, SBIM. Eurographics Association, 39--46. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Heloise Hse and A. Richard Newton. 2004. Sketched Symbol Recognition Using Zernike Moments. In Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01 (ICPR '04). IEEE Computer Society, Washington, DC, USA, 367--370. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Heloise Hwawen Hse and A Richard Newton. 2005. Recognition and beautification of multi-stroke symbols in digital ink. Computers & Graphics 29, 4 (2005), 533--546. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Gabe Johnson, Mark D. Gross, Jason Hong, and Ellen Yi-Luen Do. 2009. Computational Support for Sketching in Design: A Review. Found. Trends Hum.-Comput. Interact. 2, 1 (Jan. 2009), 1--93. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. David Johnston and Christine Alvarado. 2013. Sketch Recognition of Digital Logical Circuits. (2013).Google ScholarGoogle Scholar
  28. F. Julca-Aguilar, H. Mouchère, C. Viard-Gaudin, and N. S. T. Hirata. 2017. A General Framework for the Recognition of Online Handwritten Graphics. ArXiv e-prints (Sept. 2017).Google ScholarGoogle Scholar
  29. Levent Burak Kara and Thomas F Stahovich. 2007. Hierarchical parsing and recognition of hand-sketched diagrams. In ACM SIGGRAPH - International Conference on Computer Graphics and Interactive Techniques. ACM, 17. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Maria Karam and m. c. schraefel. 2006. Investigating User Tolerance for Errors in Vision-enabled Gesture-based Interactions. In Proceedings of the Working Conference on Advanced Visual Interfaces (AVI '06). ACM, New York, NY, USA, 225--232. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Mary LaLomia. 1994. User Acceptance of Handwritten Recognition Accuracy. In Conference Companion on Human Factors in Computing Systems (CHI '94). ACM, New York, NY, USA, 107--108. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. C Lee, Josiah Jordan, Thomas F Stahovich, and James Herold. 2012. Newtons Pen II: an intelligent, sketch-based tutoring system and its sketch processing techniques. In Proceedings of the International Symposium on Sketch-Based Interfaces and Modeling. Eurographics Association, 57--65. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Han-Lung Lin. 2014. Estimating Student Competence in Engineering Statics From a Lexical Analysis of Handwritten Equations. Thesis.Google ScholarGoogle Scholar
  34. Stephen Marsland. 2003. Novelty detection in learning systems. Neural computing surveys 3, 2 (2003), 157--195.Google ScholarGoogle Scholar
  35. Tom Ouyang and Randall Davis. 2009. Learning from neighboring strokes: Combining appearance and context for multi-domain sketch recognition. In Advances in Neural Information Processing Systems 22. 1401--1409. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Tom Y Ouyang and Randall Davis. 2007. Recognition of Hand Drawn Chemical Diagrams. In Proceedings of the 22Nd National Conference on Artificial Intelligence - Volume 1 (AAAI'07). AAAI Press, 846--851. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Tom Y Ouyang and Randall Davis. 2011. ChemInk: a natural real-time recognition system for chemical drawings. In In International Conference on Intelligent User Interfaces (IUI fi11. ACM, 267--276. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Brandon Paulson and Tracy Hammond. 2008. PaleoSketch: Accurate Primitive Sketch Recognition and Beautification. In Proceedings of the 13th International Conference on Intelligent User Interfaces (IUI '08). ACM, 1--10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Eric Jeffrey Peterson, Thomas F Stahovich, Eric Doi, and Christine Alvarado. 2010. Grouping Strokes into Shapes in Hand-Drawn Diagrams. In Proceedings of the National Conference on Artificial Intelligence. 974--979. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. Marco A.F. Pimentel, David A. Clifton, Lei Clifton, and Lionel Tarassenko. 2014. A review of novelty detection. Signal Processing 99 (2014), 215 -- 249. Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. Beryl Plimmer, Rachel Blagojevic, Samuel Hsiao-Heng Chang, Paul Schmieder, and Jacky Shunjie Zhen. 2012. Rata: codeless generation of gesture recognizers. In Proceedings of the 26th Annual BCS Interaction Specialist Group Conference on People and Computers. British Computer Society, 137--146. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. J Reaver, Thomas F Stahovich, and James Herold. 2011. How to make a quick $: Using hierarchical clustering to improve the efficiency of the dollar recognizer. In Proceedings - SBIM: ACM SIGGRAPH / Eurographics Symposium on Sketch-Based Interfaces and Modeling. ACM, 103--108. Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Dean Rubine. 1991. Specifying Gestures by Example. (1991), 329--337. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Eric Saund and Edward Lank. 2003. Stylus input and editing without prior selection of mode. In UIST: Proceedings of the Annual ACM Symposium on User Interface Softaware and Technology. ACM, 213--216. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. Tevfik Metin Sezgin and Randall Davis. 2005. HMM-based efficient sketch recognition. In Proceedings of the 10th international conference on Intelligent user interfaces. ACM, 281--283. Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. Tevfik Metin Sezgin and Randall Davis. 2007a. Sketch interpretation using multiscale models of temporal patterns. IEEE Computer Graphics and Applications 27, 1 (2007), 28--37. Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. Tevfik Metin Sezgin and Randall Davis. 2007b. Temporal Sketch Recognition in Interspersed Drawings. In Proceedings of the 4th Eurographics Workshop on Sketch-based Interfaces and Modeling (SBIM '07). ACM, New York, NY, USA, 15--22. Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. Tevfik Metin Sezgin and Randall Davis. 2008. Sketch recognition in interspersed drawings using time-based graphical models. Computers & Graphics 32, 5 (2008), 500--510. Google ScholarGoogle ScholarDigital LibraryDigital Library
  49. Michael Shilman and Paul Viola. 2004. Spatial recognition and grouping of text and graphics. In Proceedings of the First Eurographics conference on Sketch-Based Interfaces and Modeling. Eurographics Association, 91--95. Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. Michael Shilman, Paul Viola, and Kumar Chellapilla. 2004. Recognition and grouping of handwritten text in diagrams and equations. In Frontiers in Handwriting Recognition, 2004. IWFHR-9 2004. Ninth International Workshop on. IEEE, 569--574. Google ScholarGoogle ScholarDigital LibraryDigital Library
  51. Thomas F Stahovich, Eric J Peterson, and Hanlung Lin. 2014. An efficient, classification-based approach for grouping pen strokes into objects. Computers & Graphics 42 (2014), 14--30.Google ScholarGoogle ScholarCross RefCross Ref
  52. Philip C. Stevens, Rachel Blagojevic, and Beryl Plimmer. 2013. Supervised Machine Learning for Grouping Sketch Diagram Strokes. In Proceedings of the International Symposium on Sketch-Based Interfaces and Modeling (SBIM '13). ACM, New York, NY, USA, 43--50. Google ScholarGoogle ScholarDigital LibraryDigital Library
  53. Pang-Ning Tan, Michael Steinbach, and Vipin Kumar. 2005. Introduction to Data Mining, (First Edition). Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  54. Caglar Tirkaz, Berrin Yanikoglu, and T. Metin Sezgin. 2012. Sketched symbol recognition with auto-completion. Pattern Recognition 45, 11 (2012), 3926 -- 3937. Google ScholarGoogle ScholarDigital LibraryDigital Library
  55. Chengcheng Wang, Harold Mouchère, Aurélie Lemaitre, and Christian Viard-Gaudin. 2017. Online flowchart understanding by combining max-margin Markov random field with grammatical analysis. International Journal on Document Analysis and Recognition (IJDAR) 20, 2 (01 Jun 2017), 123--136. Google ScholarGoogle ScholarDigital LibraryDigital Library
  56. C. Wang, H. Mouchre, C. Viard-Gaudin, and L. Jin. 2016. Combined Segmentation and Recognition of Online Handwritten Diagrams with High Order Markov Random Field. In 2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR). 252--257.Google ScholarGoogle Scholar
  57. Jacob O Wobbrock, Andrew D Wilson, and Yang Li. 2007. Gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes. In UIST: Proceedings of the Annual ACM Symposium on User Interface Softaware and Technology. ACM, 159--168. Google ScholarGoogle ScholarDigital LibraryDigital Library
  58. Kemal Tugrul Yesilbek and T. Metin Sezgin. 2017. Sketch recognition with few examples. Computers & Graphics 69 (2017), 80 -- 91. DOI:http://dx.doi.org/ Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. The role of grouping in sketched diagram recognition

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    • Published in

      cover image ACM Conferences
      Expressive '18: Proceedings of the Joint Symposium on Computational Aesthetics and Sketch-Based Interfaces and Modeling and Non-Photorealistic Animation and Rendering
      August 2018
      200 pages
      ISBN:9781450358927
      DOI:10.1145/3229147
      • General Chairs:
      • Brian Wyvill,
      • Hongbo Fu

      Copyright © 2018 ACM

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      Publication History

      • Published: 17 August 2018

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