Decomposing intensity gradients into information about shape and material

Determination of Intensity Thresholds via Shape Gradients

Shape analysis is a vital aspect of medical imaging. The shapes of objects in an image provide high-level information that is essential for many image processing tasks. Accurate analysis of medical images is often dependent upon an appropriate greyscale thresholding of the image for reliable feature extraction. The determination of object thresholds can be a time-consuming task because the thre...

Speechreading using shape and intensity information

We describe a speechreading system that uses both, shape information from the lip contours and intensity information from the mouth area. Shape information is obtained by tracking and parameterising the inner and outer lip boundary in an image sequence. Intensity information is extracted from a grey level model, based on principal component analysis. In comparison to other approaches, the inten...

Decomposing Matrices into Blocks

In this paper we investigate whether matrices arising from linear or integer programming problems can be decomposed into so-called bordered block diagonal form. More precisely, given some matrix A, we try to assign as many rows as possible to some number β of blocks of size κ such that no two rows assigned to different blocks intersect in a common column. Bordered block diagonal form is desirab...

Converting Level Set Gradients to Shape Gradients

The level set representation of shapes is useful for shape evolution and is widely used for the minimization of energies with respect to shapes. Many algorithms consider energies depending explicitly on the signed distance function (SDF) associated with a shape, and differentiate these energies with respect to the SDF directly in order to make the level set representation evolve. This framework...

Supplementary Material for Facial Expression Intensity Estimation Using Ordinal Information