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Robust global translation averaging with feature tracks
Cui Hainan(崔海楠); Shen Shuhan(申抒含); Hu Zhanyi(胡占义)
2016
会议名称International Conference on Pattern Recognition
会议日期2016-11
会议地点Mexico
摘要How to average translations is the single most difficult task in global structure-from-motion (SfM) to fully tap its potentials in terms of reconstruction efficiency and accuracy since usually only noisy translation directions can be factored out from essential matrices due to the inevitable matching outliers. To tackle this problem, this work proposes a two-step strategy. Firstly, a “2-point method” is introduced to refine the epipolar geometry by which a more accurate track set is generated. Then, translation lengths are computed by solving a convex L1 optimization according to the adjacent triangles induced by the selected tracks and translations. Extensive experiments show that our method performs similarly or better than the state-of-art SfM approaches in terms of the reconstruction accuracy, completeness and efficiency. 
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/19767
专题模式识别国家重点实验室_机器人视觉
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GB/T 7714
Cui Hainan,Shen Shuhan,Hu Zhanyi. Robust global translation averaging with feature tracks[C],2016.
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