For Motion Picture Special Effects, it is often necessary to take a source image of an acto& segment the actor from the unwanted background, and then composite over a new background. The standard approach requires the unwanted background to be a blue screen. While this technique is capable of handling areas where the foreground blends into the background, the physical requirements present many practical problems. This paper presents an algorithm that requires minimal human interaction to segment Motion Picture resolution images and image sequences. We show that it can be used not only to segment badly lit or noisy bluescreen images, but also to segment actors where the background is more varied.
In this paper, an improved method for eye extraction using deformable templates is proposed. This new method overcomes the shortcomings of traditional deformable template techniques for eye extraction, such as unexpected shrinking of the template and complexity of the updating procedure, while offering higher flexibility and accuracy. A new size term and eye corner finder are introduced to prevent over-shrinking and improve speed and accuracy of fitting. The eye features are fitted in a pre-set order to reduce the complexity of the updating procedure and increase the flexibility. We demonstrate the success of this new method by extracting eye features in real images.
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