In this paper, we propose a Multi-Manifold Discriminant Analysis (MMDA) method for an image feature extraction and pattern recognition based on graph embedded learning and under the Fisher discriminant analysis framework. In an MMDA, the within-class graph and between-class graph are, respectively, designed to characterize the within-class compactness and the between-class separability, seeking...

We present a Multi-Resolution Dual method based on an incremental octree-based refinement strategy. Our solution is able to generate multi-resolution surfaces from segmented volumetric data. It extends the Dual Marching Cubes algorithm over a generalized octree and guarantees that the produced surfaces are always manifold by introducing a new cell-based criterion for dual vertices generation. M...

We introduce a set of tools for interactive modeling of multi-material objects. We use non-manifold surface meshes to define complex objects, which can have multiple connected solid regions of different materials. Our suite of tools can create and edit non-manifold surfaces, while maintaining a consistent labeling of distinct regions. We also introduce a technique for generating approximate mat...

Thulium salts and complexes are shown to be emissive from three states in the excited state manifold of Tm(3+). Formation of the (1)D(2) state can result in luminescence, or in energy transfer to the lower energy (1)G(4) and (3)H(4) emissive states. Where chromophores are present in the ligand structure, emission is restricted to thulium centred emissive states that are lower in energy than the...

Facial-expression data often appear in multiple views either due to head-movements or the camera position. Existing methods for multi-view facial expression recognition perform classification of the target expressions either by using classifiers learned separately for each view or by using a single classifier learned for all views. However, these approaches do not explore the fact that multi-vi...