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Improving human computer interaction in a classroom environment using computer vision
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Improving human computer interaction in a classroom environment using computer vision
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International Conference on Intelligent User Interfaces
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Proceedings of the 5th international conference on Intelligent user interfaces
table of contents
New Orleans, Louisiana, United States
Pages: 86 - 93
Year of Publication: 2000
ISBN:1-58113-134-8
Authors
Joshua Flachsbart
Intelligent Information Laboratory, Northwestern University, 1890 Maple Avenue, Evanston, IL
David Franklin
Intelligent Information Laboratory, Northwestern University, 1890 Maple Avenue, Evanston, IL
Kristian Hammond
Intelligent Information Laboratory, Northwestern University, 1890 Maple Avenue, Evanston, IL
Sponsors
SIGCHI:
ACM Special Interest Group on Computer-Human Interaction
SIGART:
ACM Special Interest Group on Artificial Intelligence
Publisher
ACM
New York, NY, USA
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Downloads (6 Weeks): 2, Downloads (12 Months): 68, Citation Count: 3
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ABSTRACT
In this paper we discuss our use of multi-modal input to improve human computer interaction. Specifically we look at the methods used in the Intelligent Classroom to combine multiple input modes, and examine in particular the visual input modes. The Classroom provides context that improves the functioning of the visual input modes. It also determines which visual input modes are needed when. We examine a number of visual input modes to see how they fit into the general scheme, and look at how the Classroom controls their operation.
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
Aloimonos, Y. Purposive and qualitative active vision. In Proceedings on the International Conference on Pattern Recognition, pages 346-360, 1990
2
David Chapman, Vision, instruction, and action, MIT Press, Cambridge, MA, 1991
3
Firby, R. J., Kahn, R. E., Prokopowicz, P. N., and Swain, M. J. An architecture for vision and action. In Proceedings on the International Joint Conference on Artificial Intelligence, 1995
4
Flachsbart, J. Gargoyle: Vision in the Intelligent Classroom. Master's thesis, University of Chicago, 1997.http://www.cs.uchicago.edu/-joshfficial~content /Papers.html
5
Franklin, D., and Flachsbart, J. All gadget and no representation makes Jack a dull environment. Technical Report SS-98-02, American Association for Artificial Intelligence, 1998.
6
David Franklin, Cooperating with people: the intelligent classroom, Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence, p.555-560, July 1998, Madison, Wisconsin, United States
7
Ian D. Horswill, Specialization of perceptual processes, Massachusetts Institute of Technology, Cambridge, MA, 1993
8
Roger Ewing Kahn , Michael J. Swain, Perseus: an extensible vision system for human-machine interaction, 1996
9
Pinhanez, C., and Bobick, A. Intelligent Studios: Using computer vision to control TV cameras. IJCAZ Workshop on Entertainment and AUAZife, April 1995.
10
Saund, E. 1996. Machine interpretation of diagrammatic user interfaces to office whiteboard appliances. Technical Report, Xerox PARC, 1996.
11
Thomas M. Strat, Natural object recognition, Springer-Verlag New York, Inc., New York, NY, 1992
12
Glenn Wasson , David Kortenkamp , Eric Huber, Integrating active perception with an autonomous robot architecture, Proceedings of the second international conference on Autonomous agents, p.325-331, May 10-13, 1998, Minneapolis, Minnesota, United States
[doi>10.1145/280765.280850]
13
Wren, C., Azarbayejani, A., Darrell, T., and Pentland A. Pfinder: Real time tracking of the human body. Media Lab Tech Report 353, Massachusetts Institute of Technology, 1995.
CITED BY 3
Michael Hellenschmidt, Distributed implementation of a self-organizing appliance middleware, Proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies, October 12-14, 2005, Grenoble, France
David Franklin , Jay Budzik , Kristian Hammond, Plan-based interfaces: keeping track of user tasks and acting to cooperate, Proceedings of the 7th international conference on Intelligent user interfaces, January 13-16, 2002, San Francisco, California, USA
Will Fitzgerald , R. James Firby , Michael Hannemann, Multimodal event parsing for intelligent user interfaces, Proceedings of the 8th international conference on Intelligent user interfaces, January 12-15, 2003, Miami, Florida, USA
INDEX TERMS
Primary Classification:
I.
Computing Methodologies
I.5
PATTERN RECOGNITION
Additional Classification:
I.
Computing Methodologies
I.2
ARTIFICIAL INTELLIGENCE
Keywords:
computer vision,
context-based vision,
intelligent environments,
multi-modal input
Collaborative Colleagues:
Joshua Flachsbart: colleagues
David Franklin: colleagues
Kristian Hammond: colleagues
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