Multi-scale mesh saliency with local adaptive patches for viewpoint selection

To prove the optimal convergence of the standard finite element method, we shall construct a modification of the nodal interpolation operator replacing the standard

In this section, we present the resulting maps obtained on the spectral images and we discuss the similarity of the SS with the Signature-based Visual Saliency model (SVS) presented

We proposed a new band selection method based on saliency maps for the dimensionality reduction of spec- tral image.. A simple metric based on

Figure 6 shows the original objects and the watermarked ones. It can be seen that the distortion is negligible and cannot be noticed by the human eye thanks to the use mesh saliency

Motivated by these observations, we propose to learn the discriminative spatial saliency of im- ages while simultaneously learning a max margin classifier for a given

Comparison with the state-of-the-art: image (a) shows the original 3D object dinosaur (21 777 vertices), image (b) shows its saliency by our method (ε = 0.013 and l=17), image (c)

To compute the local statisticsthat reflect the structural infor- mation of a 3D mesh, we use our multi-scale saliency map as a basis. Indeed, given a rough and a smooth re- gion,

The central objective of this work is to propose eective methods for the segmentation of images with intensity inhomogeneities. To this end, we have studied the recently proposed