Depth map color constancy

Abstract A human observer is able to determine the color of objects independent of the light illuminating these objects. This ability is known as color constancy. In the first stages of visual information processing, data are analyzed with respect to wavelength composition, orientation, motion, and depth. With this contribution, we investigate whether depth information can help in estimating the color of the objects. We assume that local space average color is computed in V4 through resistively coupled neurons to estimate the color of the illuminant. We show how this computational model can be extended to incorporate depth information.

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