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A Multi-view Dimensionality Reduction Algorithm Based on Smooth Representation Model
The proposed method aims to find a subspace for the high-dimensional data, in which the smooth reconstructive weights are preserved as much as possible.
Non-rigid 3D shape retrieval based on multi-view metric learning
The different intrinsic representations (features) focus on different geometric properties to describe the same 3D shape, which makes the representations are related.
Multi-feature Distance Metric Learning for Non-rigid 3D Shape Retrieval
To address these issue, a novel multi-feature distance metric learning method for non-rigid 3D shape retrieval is presented in this study, which can make full use of the complimentary geometric information from multiple shape features by utilizing the KL-divergences.
Auto-weighted Mutli-view Sparse Reconstructive Embedding
Therefore, it is essential to fully exploit the complementary information embedded in multiple views to enhance the performances of many tasks.
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