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Facial landmark detection is a challenging task with broad applications. Many approaches have been proposed with varying degrees of success. Regression based methods update the facial point positions iteratively. The mean shape or shapes sampled from training set is often used as the initialization, which sometimes may lead to a local minimum in update due to the offset of initial positions and target...
Predictive modeling aims at constructing models that predict a target property of an object based on its descriptions. In digital human modeling, it can be applied to predicting human body shape from images, measurements, or descriptive features. While images and measurements can be converted to numerical values, it is difficult to assign numerical values to descriptive features and therefore regression...
Univariate anthropometric data have long documented a difference in head shape proportion between Chinese and Caucasian populations. This difference has made it impossible to create eyewear, helmets and facemasks that fit both groups well. However, it has been unknown to what extend and precisely how the two populations differ from each other in form. In this study, we applied geometric morphometrics...
We propose a posture invariant surface descriptor for triangular meshes. Using intrinsic geometry, the surface is first transformed into a representation that is independent of the posture. Spin image is then adapted to derive a descriptor for the representation. The descriptor is used for extracting surface features automatically. It is invariant with respect to rigid and isometric deformations,...
We present an algorithm to predict landmarks on 3D human scans in varying poses. Our method is based on learning bending-invariant landmark properties. We also learn the spatial relationships between pairs of landmarks using canonical forms. The information is modeled by a Markov network, where each node of the network corresponds to a landmark position and where each edge of the network represents...
We find dense point-to-point correspondences between two surfaces corresponding to different postures of the same articulated object in a fully automatic way. The approach requires no prior knowledge about the shapes being registered. Furthermore, the approach does not require any user-specified parameters. We register possibly incomplete triangular meshes. We model the deformations of an object as...
We introduce a new bending invariant representation of a triangular mesh S. The bending invariant mesh X of S is a deformation of S that has the property that the geodesic distance between each pair of vertices on S is approximated well by the Euclidean distance between the corresponding vertices on X. Furthermore, X is intersection-free. The main advantage of the bending invariant mesh compared to...
We study the behaviorally important task of gender classification based on the human body shape. We propose a new technique to classify by gender human bodies represented by possibly incomplete triangular meshes obtained using laser range scanners. The classification algorithm is invariant of the posture of the human body. Geodesic distances on the mesh are used for classification. Our results indicate...
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