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ICCV
2011
IEEE

Multiclass Recognition and Part Localization with Humans in the Loop

12 years 6 months ago
Multiclass Recognition and Part Localization with Humans in the Loop
We propose a visual recognition system that is designed for fine-grained visual categorization. The system is composed of a machine and a human user. The user, who is unable to carry out the recognition task by himself, is interactively asked to provide two heterogeneous forms of information: clicking on object parts and answering binary questions. The machine intelligently selects the most informative question to pose to the user in order to identify the object’s class as quickly as possible. By leveraging computer vision and analyzing the user responses, the overall amount of human effort required, measured in seconds, is minimized. We demonstrate promising results on a challenging dataset of uncropped images, achieving a significant average reduction in human effort over previous methods.
Catherine Wah, Steven Branson, Pietro Perona, Serg
Added 11 Dec 2011
Updated 11 Dec 2011
Type Journal
Year 2011
Where ICCV
Authors Catherine Wah, Steven Branson, Pietro Perona, Serge Belongie
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