Accurate 3D shape estimation based on combinatorial optimization

Authors:
Seong-O Shim;Tae-Sun Choi
Affiliations:
Signal and Image Processing Lab, School of Information and Mechatronics, Gwangju Institute of Science and Technology, Gwangju, South Korea;Signal and Image Processing Lab, School of Information and Mechatronics, Gwangju Institute of Science and Technology, Gwangju, South Korea
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 6
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Abstract

The problem of estimating the three-dimensional (3D) geometry of an object from a sequence of images obtained at different focus settings is called shape from focus (SFF). The conventional SFF methods apply focus measure operator at each pixel using neighboring pixels in the same image frame. However, for an object with complex geometry, such methods cannot compute accurate focus level of a pixel, since the neighboring pixels in an image, taken with small depth of field, do not have the same focus level. In this paper, a novel SFF algorithm based on combinatorial optimization is proposed. After the rough estimate of the shape, we refine the shape iteratively by searching the optimal focus measure of each pixel using neighboring pixels on various image frames. The proposed SFF algorithm shows improvements in both the accuracy of the shape and the computational complexity in comparison to the previous SFF methods.