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Acquiring 3-D Models from Sequences of Contours
February 1994 (vol. 16 no. 2)
pp. 163-178

This paper explores shape from contour for acquiring 3-D graphics models. In this method, a continuous sequence of images is taken as an object rotates. A smooth convex shape can be estimated instantaneously from its contour and by the first derivative of contour movement (trace of contour, or contour distribution with time). We also analyze shapes that do not satisfy the conditions of smoothness and visibility, which are indispensable for modeling an object. A region that does not expose as contour yields a nonsmoothness in the tracked contour movement. We can thus detect such a region by contour distribution filtering and extract its accurate location by computing the left and right derivatives of the distribution. This has not been studied previously. These unknown regions are obtained for further investigation using other visual cues. A general approach for building a geometrical object model using contours is then described. The entire process from silhouettes to a 3-D model is based local computation; this is promising for producing shapes in real time. Our direct goal is to establish 3-D graphics models of human faces for the growing needs of visual communications. We have obtained some good results.

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Index Terms:
image sequences; filtering and prediction theory; 3-D graphics models acquisition; contour sequences; shape from contour; image sequence; smooth convex shape; tracked contour movement; contour distribution filtering; geometrical object
Citation:
J.Y. Zheng, "Acquiring 3-D Models from Sequences of Contours," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, no. 2, pp. 163-178, Feb. 1994, doi:10.1109/34.273734
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