文章基本信息

标题：Fast Projective Reconstruction: Toward Ultimate Efficiency
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作者：Hanno Ackermann ; Kenichi Kanatani
期刊名称：Information and Media Technologies
电子版ISSN：1881-0896
出版年度：2008
卷号：3
期号：2
页码：432-442
DOI：10.11185/imt.3.432
出版社：Information and Media Technologies Editorial Board
摘要：We accelerate the time-consuming iterations for projective reconstruction, a key component of self-calibration for computing 3-D shapes from feature point tracking over a video sequence. We first summarize the algorithms of the primal and dual methods for projective reconstruction. Then, we replace the eigenvalue computation in each step by the power method. We also accelerate the power method itself. Furthermore, we introduce the SOR method for accelerating the subspace fitting involved in the iterations. Using simulated and real video images, we demonstrate that the computation sometimes becomes several thousand times faster.