Research on target shape modeling based on local linear gaussian process latent variable model

A multi-view target shape modeling method based on local linear gaussian process latent variable model (LL-GPLVM) was proposed which could learn a shape manifold from a set of 2D shapes for 3D target modeling. LL-GPLVM was used to learn a view manifold for the target, in which shape was used for feature representation, a hemisphere was used as topology constrain for mani fold learning. The prior of the manifold structure was involved in manifold learning through local linear embedding, so the final manifold was the balanced result of data and topology prior, and was a probabilistic model. Experiment on synthetic data demonstrates the advantages of the proposed method over existing techniques.