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Structure from motion using sequential Monte Carlo methods
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DOI：10.1023/B:VISI.0000020669.68126.4b.png)
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Abstract
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In this paper, the structure from motion (SfM) problem is addressed using sequential Monte Carlo methods. A new SfM algorithm based on random sampling is derived to estimate the posterior distributions of camera motion and scene structure for the perspective projection camera model. Experimental results show that challenging issues in solving the SfM problem, due to erroneous feature tracking, feature occlusion, motion/structure ambiguity, mixed-domain sequences, mismatched features, and independently moving objects, can be well modeled and effectively addressed using the proposed method.
Keywords:
structure from motion
sequential Monte Carlo methods
video analysis
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