Decomposition of shapes into (approximate) convex parts is essential for applications such as part-based shape representation, shape matching, and collision detection. In this paper, we propose a novel convex decomposition using a parametric implicit shape model called Disjunctive Normal Shape Model (DNSM). The DNSM is formed as a union of polytopes which themselves are formed by intersections ...

An improvement of the Active Shape procedure introduced by Cootes and Taylor is presented. The new automated brain segmenta-tion and interpretation approach incorporates a priori knowledge about neuroanatomic structures and their speciic structural relationships to provide robust segmentation and labeling. The method was trained in 8 MR brain images and tested in 19 brain images by comparison t...

The generative surface reconstruction problem can be stated like this: Given a finite collection of 3D shapes, create a small set of functions that can be combined to generate the given shapes procedurally. We propose generative fact labeling (GFL) as an attempt to organize the iterative process of shape analysis and shape synthesis in a systematic way. We present our results for the reconstruc...

The combination of long established techniques in morphometrics with novel shape modeling approaches in geometry processing has opened new ways of visualizations of shape variability in different application areas like biology, medicine, epidemiology and agriculture. For the first time highly resolved 3D representations became accessible for statistical analysis as well as visualizations. In or...

Uniaxial stretch is an important biophysical regulator of cell morphology (or shape) and functions of vascular endothelial cells (ECs). However, it is unclear whether and how cell shape can independently regulate EC mechanotransductive properties under uniaxial stretch. Herein, utilizing a novel uniaxial cell-stretching device integrated with micropost force sensors, we reported the first exper...

In this paper, a novel Example-based Shape Learning (ESL) strategy has been proposed for facial feature alignment. The method is motivated by an intuitive and experimental observation that there exists an approximate linearity relationship between the image difference and the shape difference, that is, similar face images imply similar face shapes. Therefore, given a learning set of face images...

a r t i c l e i n f o a b s t r a c t Keywords: Saliency Low-rank and sparse analysis Shape feature Structure This paper advocates a novel multi-scale mesh saliency method using the powerful low-rank and sparse analysis in shape feature space. The technical core of our approach is a new shape descriptor that embraces both local geometry information and global structure information in an integra...

A novel method that allows the development of surface point based three-dimensional statistical shape models is presented. Given a set of medical objects, a statistical shape model can be obtained by Principal Component Analysis. This technique requires that a set of complex shaped objects is represented as a set of vectors that uniquely determine the shapes of the objects, and at the same time...

We propose a novel 3D shape parameterization by surface patches, that are oriented by 3D mesh quadrangulation of the shape. By encoding 3D surface detail on local patches, we learn a patch dictionary that identifies principal surface features of the shape. Unlike previous methods, we are able to encode surface patches of variable size as determined by the user. We propose novel methods for dict...

Two experiments explore children's spontaneous labeling of novel objects as a method to study early lexical access. The experiments also provide new evidence on children's attention to object shape when labeling objects. In Experiment 1, the spontaneous productions of 21 23- to 28-month-olds (mean 26;28) shown a set of novel, unnamed objects were analyzed both in terms of the specific words sai...