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Erschienen in:
2005 | OriginalPaper | Buchkapitel
3D Model Generation from Image Sequences Using Global Geometric Constraint
verfasst von : Masayuki Mukunoki, Kazutaka Yasuda, Naoki Asada
Erschienen in: Advances in Visual Computing
Verlag: Springer Berlin Heidelberg
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This paper describes a method for generating a three-dimensional model from an uncalibrated image sequence taken around an object. Our method is based on feature tracking and minimization of re-projection errors. To cope with mis-matchings in the result of feature tracking, we introduce two types of global geometric constraints. The one is “affine constraint” which imposes the positional relationship between pixels on the images. The other is “depth constraint” which imposes the three-dimensional structure of the object. First, we use the affine constraint to reconstruct the object roughly and then we refine the feature tracking and shape reconstruction using the depth constraint. Experimental results show that our method can automatically generate accurate three-dimensional models from real image sequences.