Taku Yokoyama

AutoKey: human assisted key extraction

Key extraction is an inverse problem of finding the foreground, the background, and the alpha from an image and some hints. Although the chromakey solves this for a limited case (single background color), this is often too restrictive in practical situations. When the extraction from arbitrary background is necessary, this is currently done by a time consuming manual task. In order to reduce the operator load, attempts have been made to assist operators using either color space or image space information. However, existing approaches have their limitations. Especially, they leave too much work to operators. In this paper, we present a key extraction algorithm which for the first time, addresses the problem quantitatively. We first derive a partial differential equation that relates the gradient of an image to the alpha values. We then describe an efficient algorithm that provides the alpha values as the solution of the equation. Along with our accurate motion estimation technique, it produces correct alpha values almost everywhere, leaving little work to operators. We also show that a careful design of the algorithm and the data representation greatly improves human interaction. At every step of the algorithm, human interaction is possible and it is intuitive. CR Categories: I.3.3 [Computer Graphics]: Picture / Image Generation; I.4.6 [Image Processing]: Segmentation Edge and feature detection; I.4.7 [Image Processing]: Feature Measurement; I.5.2 [Pattern Recognition]: Design Methodology Feature evaluation and selection. Additional

Key extraction by image differentiation

Key extraction is an inverse problem of finding the foreground, the background, and the alpha value from an image and some hints. Although the chromakey solves this for a limited case (single background color), this is often too restrictive in practical situations. When the extraction from an arbitrary background is necessary this is currently done by a time consuming manual task. To solve the problem, an algorithm must address the unique requirements of the key extraction: high resolution, analytically correct alpha values, and easy human interaction. We present an image differentiation method which, for the first time, fulfills these requirements.