Statistical shape analysis in a Bayesian framework for shapes in two and three dimensions
arXiv:1802.10570v1
Originality Incremental advance
AI Analysis
This addresses shape analysis for researchers in fields like computer vision or medical imaging, but appears incremental as it adapts Bayesian frameworks to shape data.
The authors tackled shape classification by developing a novel Bayesian method for 2D and 3D data, evaluating it on the Kimia shape database for 2D cases.
In this paper, we describe a novel shape classification method which is embedded in the Bayesian paradigm. We discuss the modelling and the resulting shape classification algorithm for two and three dimensional data shapes. We conclude by evaluating the efficiency and efficacy of the proposed algorithm on the Kimia shape database for the two dimensional case.