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Scene Gist Categorization from Perceptual Relations
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Humans has this remarkable ability to comprehend visual scenes rapidly and accurately. Whether we quickly change television
channels, browse photo albums, or simply trying to cross the road, our visual system is working with superb efficiency, accuracy, and speed
to extract the meaning of each scene. Examine the rapid sequence of scenes on the right. Is it fair to say that you can indeed grasp the gist of most?
But what characterizes visual processing underlying this visual categorization process?
In this project we focus on one aspect of this question related to prior knowledge about the
perceptual relations between the different scene categories.
To date, computational algorithms for scene categorization rarely consider the possible effect of such perceptual relations.
However, even intuitively, when our visual system observes a bedroom scene for a fraction of a second and "deliberates" how to categorize it, what possibly comes to mind in addition to
"bedroom" are perhaps classes like "living room" or "kitchen". It appears as if our visual system does not even consider possibilities such as "coast" or "highway", or more generally, scenes
which are perceptually "distant" from the observable reference class. Put differently, prior knowledge about the perceptual relations between the different categories of scenes may help
facilitate better, more efficient, and faster categorization.
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The formal manifestation of the basic idea described above requires the extraction of the perceptual relations between
scene classes. While we use controlled lab experiments to collect these data for small number of classes (see papers), doing the same
with larger sets becomes infeasible without an enormous number of subjects, something that may only be possible by harnesting
the power of the web. We therefore invite you to play our perceptual game and contribute to this data collection
ins a Pair-Matching Categorization (PMC) experiment. Please click on the image on the left to begin.
Please note that the web-based experiment requires a web browser and just 4-5 short minutes of your time.
(Unfortunately, at this point the software is supported on Windows platforms only).
We greatly appreciate your participation and we thank you for helping the collection of these data.
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Papers and Presentations
- I. Kadar, and O. Ben-Shahar,
Small Sample Scene Categorization from Perceptual Relations
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In the Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
Providence, Rhode Island, 2012.
- I. Kadar, and O. Ben-Shahar,
Learning perceptual relations for categorizing natural scenes from few training examples
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In the Annual meeting of the Vision Science Society (VSS),
Naples, Florida, 2012.
- I. Kadar, and O. Ben-Shahar,
A new perceptual paradigm and psychophysical evidence for hierarchical gist recognition
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In the Annual meeting of the Vision Science Society (VSS),
Naples, Florida, 2011.
Who and Where...
Acknowledgments
This work was funded in part by the European Commission in the 7th Framework Programme (CROPS GA no 246252).
We also thank the generous support of the Frankel fund,
the Paul Ivanier center for Robotics Research and
the Zlotowski Center for Neuroscience
at Ben-Gurion University.
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