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Improving visual search with image segmentation
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Conference on Human Factors in Computing Systems archive
Proceedings of the 27th international conference on Human factors in computing systems table of contents
Boston, MA, USA
SESSION: Visualization 1 table of contents
Pages 1093-1102  
Year of Publication: 2009
ISBN:978-1-60558-246-7
Authors
Clifton Forlines  Mitsubishi Electric Research Labs, University of Toronto, Cambridge, USA
Ravin Balakrishnan  University of Toronto, Toronto, Canada
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

People's ability to accurately locate target objects in images is severely affected by the prevalence of the sought objects. This negative effect greatly impacts critical real world tasks, such as baggage screening and cell slide pathology, in which target objects are rare. We present three novel image presentation techniques that are designed to improve visual search. Our techniques rely on the images being broken into image segments, which are then recombined or displayed in novel ways. The techniques and their underlying design reasoning are described in detail, and three experiments are presented that provide initial evidence that these techniques lead to better search performance in a simulated cell slide pathology task.


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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Collaborative Colleagues:
Clifton Forlines: colleagues
Ravin Balakrishnan: colleagues