ACM Home Page
Please provide us with feedback. Feedback
A perceptually-supported sketch editor
Full text PdfPdf (799 KB)
Source Symposium on User Interface Software and Technology archive
Proceedings of the 7th annual ACM symposium on User interface software and technology table of contents
Marina del Rey, California, United States
Pages: 175 - 184  
Year of Publication: 1994
ISBN:0-89791-657-3
Authors
Eric Saund  Xerox Palo Alto Research Center, 3333 Coyote Hill Rd., Palo Alto, CA
Thomas P. Moran  Xerox Palo Alto Research Center, 3333 Coyote Hill Rd., Palo Alto, CA
Sponsors
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
SIGSOFT: ACM Special Interest Group on Software Engineering
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 4,   Downloads (12 Months): 33,   Citation Count: 26
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues   peer to peer  

Tools and Actions: Review this Article  
Save this Article to a Binder    Display Formats: BibTex  EndNote ACM Ref   
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/192426.192494
What is a DOI?

ABSTRACT

The human visual system makes a great deal more of images than the elemental marks on a surface. In the course of viewing, creating, or editing a picture, we actively construct a host of visual structures and relationships as components of sensible interpretations. This paper shows how some of these computational processes can be incorporated into perceptually-supported image editing tools, enabling machines to better engage users at the level of their own percepts. We focus on the domain of freehand sketch editors, such as an electronic whiteboard application for a pen-based computer. By using computer vision techniques to perform covert recognition of visual structure as it emerges during the course of a drawing/editing session, a perceptually supported image editor gives users access to visual objects as they are perceived by the human visual system. We present a flexible image interpretation architecture based on token grouping in a multiscale blackboard data structure. This organization supports multiple perceptual interpretations of line drawing data, domain-specific knowledge bases for interpretable visual structures, and gesture-based selection of visual objects. A system implementing these ideas, called PerSketch, begins to explore a new space of WYPIWYG (What You Perceive Is What You Get) image editing tools.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
Lee, S. Recognizing Hand-Drawn Electrical Circuit Symbols with Attributed Graph Matching. In H. S. Baird, H. Bunke, and K. Yamamoto (eds.), Structured Document Image Analysis. Springer-Verlag, New York, 1992.
 
3
Mart, D. Early Processing of Visual Information. Phil. Trans. R. Soc. Lond., B 275 (1976), 483-519.
 
4
 
5
Montalvo, F. Diagram Understanding: The Symbolic Descriptions Behind the Scenes. In T. ichikawa, E. Jungert, and R. Korfhage (eds.), Visual Languages and Applications. Plenum Press, New York, 1990.
 
6
Moran, T. Deformalizing Computer and Communication Systems. Position Paper for the InterCHI93 Research Symposium. 1993.
 
7
Okazaki, S., and Tsuji, Y. An Adaptive Recognition Method for Line Drawings Using Construction Rules. NEC Research and Development Journal, 92 (1989).
8
 
9
 
10
Sato, T., and Tojo, A. Recognition and Understanding of Hand-Drawn Diagrams. Proc. 6th International Conference on Pattern Recognition. IEEE Computer Society Press, New Jersey, 1982.
 
11
 
12

CITED BY  26
 
 
 
 
 
 

Collaborative Colleagues:
Eric Saund: colleagues
Thomas P. Moran: colleagues

Peer to Peer - Readers of this Article have also read: