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Shape Recipes: Scene Representations that Refer to the Image

Author(s)
Freeman, William T.; Torralba, Antonio
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Abstract
The goal of low-level vision is to estimate an underlying scene, given an observed image. Real-world scenes (e.g., albedos or shapes) can be very complex, conventionally requiring high dimensional representations which are hard to estimate and store. We propose a low-dimensional representation, called a scene recipe, that relies on the image itself to describe the complex scene configurations. Shape recipes are an example: these are the regression coefficients that predict the bandpassed shape from bandpassed image data. We describe the benefits of this representation, and show two uses illustrating their properties: (1) we improve stereo shape estimates by learning shape recipes at low resolution and applying them at full resolution; (2) Shape recipes implicitly contain information about lighting and materials and we use them for material segmentation.
Date issued
2002-09-01
URI
http://hdl.handle.net/1721.1/6704
Other identifiers
AIM-2002-016
Series/Report no.
AIM-2002-016
Keywords
AI, scene representation, shape, stereo, shape recipes

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