Abstract

We propose a novel method to analyze a sequence of color images. A series of color images is examined in a four-dimensional space, which we call the temporal-color space, whose axes are the three color axes red, green, and blue and one temporal axis. The significance of the temporal-color space lies in its ability to represent the change of image color with time. A conventional color space analysis yields a histogram of the colors in an image, only for an instant of time. Conceptually, the two reflection components from the dichromatic-reflection model, the specular-reflection component and the body-reflection component, form two subspaces in temporal-color space. These two components can be extracted at each pixel in the image locally. Using this fact, we analyzed real color images and separated the two reflection components successfully. We did not make any assumptions about surface properties or the global distribution of surface normals. Finally, object shape was recovered.

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