Density Adaptive Point Set Registration

Järemo Lawin, FelixLinköpings universitet,Datorseende,Tekniska fakulteten (författare)

Funding Agencies|EUs Horizon 2020 Programme [644839]; CENIIT grant [18.14]; VR grant: EMC2 [2014-6227]; VR grant [2016-05543]; VR grant: LCMM [2014-5928]
Probabilistic methods for point set registration have demonstrated competitive results in recent years. These techniques estimate a probability distribution model of the point clouds. While such a representation has shown promise, it is highly sensitive to variations in the density of 3D points. This fundamental problem is primarily caused by changes in the sensor location across point sets. We revisit the foundations of the probabilistic registration paradigm. Contrary to previous works, we model the underlying structure of the scene as a latent probability distribution, and thereby induce invariance to point set density changes. Both the probabilistic model of the scene and the registration parameters are inferred by minimizing the Kullback-Leibler divergence in an Expectation Maximization based framework. Our density-adaptive registration successfully handles severe density variations commonly encountered in terrestrial Lidar applications. We perform extensive experiments on several challenging real-world Lidar datasets. The results demonstrate that our approach outperforms state-of-the-art probabilistic methods for multi-view registration, without the need of re-sampling.

Danelljan, Martin,1989-Linköpings universitet,Datorseende,Tekniska fakulteten(Swepub:liu)marda26 (författare)
Khan, Fahad Shahbaz,1983-Linköpings universitet,Datorseende,Tekniska fakulteten(Swepub:liu)fahkh30 (författare)
Forssén, Per-Erik,1973-Linköpings universitet,Datorseende,Tekniska fakulteten(Swepub:liu)perfo51 (författare)
Felsberg, Michael,1974-Linköpings universitet,Datorseende,Tekniska fakulteten(Swepub:liu)micfe03 (författare)
Linköpings universitetDatorseende (creator_code:org_t)

Ingår i:2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition: IEEE, s. 3829-38379781538664209

Av författaren/redakt...: Järemo Lawin, Fe ...; Danelljan, Marti ...; Khan, Fahad Shah ...; Forssén, Per-Eri ...; Felsberg, Michae ...

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