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Exploring bimanual camera control and object manipulation in 3D graphics interfaces
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Source Conference on Human Factors in Computing Systems archive
Proceedings of the SIGCHI conference on Human factors in computing systems: the CHI is the limit table of contents
Pittsburgh, Pennsylvania, United States
Pages: 56 - 62  
Year of Publication: 1999
ISBN:0-201-48559-1
Authors
Ravin Balakrishnan  Dept. of Computer Science, University of Toronto, Toronto, Ontario, Canada M5S 3G4 and Aliaslwavefront, 210 King Street East, Toronto, Ontario, Canada M5A 1J7
Gordon Kurtenbach  Aliaslwavefront, 210 King Street East, Toronto, Ontario, Canada M5A 1J7
Sponsor
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 16,   Downloads (12 Months): 62,   Citation Count: 23
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ABSTRACT

We explore the use of the non-dominant hand to control a virtual camera while the dominant hand performs other tasks in a virtual 3D scene. Two experiments and an informal study are presented which evaluate this interaction style by comparing it to the status-quo unimanual interaction. In the first experiment, we find that for a target selection task, performance using the bimanual technique was 20% faster. Experiment 2 compared performance in a more complicated object docking task. Performance advantages are shown, however, only after practice. Free-form 3D painting was explored in the user study. In both experiments and in the user study participants strongly preferred the bimanual technique. The results also indicate that user preferences concerning bimanual interaction may be driven by factors other than simple time-motion performance advantages.


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.

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Braunstein, M.L. (1976). Depth perception through motion. Academic Press.
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Cutting, J.E. (1986). Perception with an eye for motion, MIT Press.
 
7
Guiard, Y. (1987). Asymmetric division of labour in human skilled bimanual action: The kinematic chain as a model. Journal of Motor Behaviour, 19, 486-517.
 
8
Haber, R.N., & Hershenson, M. (1973). The psychology of visual perception. Holt, Rinehart, and Winston.
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10
11
 
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johnsgard, T. (1994). Fitts' Law with a virtual reality glove and a mouse: Effects of gain. Proceedings of Graphics Interface 1994, 8-15, Canadian Information Processing Society.
13
 
14
Kirsh, D. & Maglio, P. (1994). On distinguishing epistemic from pragmatic action. Cognitive Science, 18(4), 513-549.
15
16
 
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Multigen Inc., SmartScene. http://www.multigen.com/
 
18
Poulton, E.C. (1989). Bias in quantifying judgements. Lawrence Erlbaum Associates.
 
19
20
 
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Wickens, C.D., Todd, S., & Seidler, K. (1989). Three dimensional displays: Perception, implementation, and applications. CSERIAC Rep: CSERIAC-SOAR-89-O01. Wright-Patterson Air Force Base, Ohio.
 
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Wickens, C.D. (1992). Engineering psychology and human performance. Harper Collins.
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CITED BY  23
 
 
 
 
 
 
 

Collaborative Colleagues:
Ravin Balakrishnan: colleagues
Gordon Kurtenbach: colleagues

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